Date: 2019-12-26 01:30:50 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 17541 rows and 500 columns.
#> Top rows are extracted by 'SD, CV, MAD, ATC' methods.
#> Subgroups are detected by 'hclust, kmeans, skmeans, pam, mclust, NMF' method.
#> Number of partitions are tried for k = 2, 3, 4, 5, 6.
#> Performed in total 30000 partitions by row resampling.
#>
#> Following methods can be applied to this 'ConsensusPartitionList' object:
#> [1] "cola_report" "collect_classes" "collect_plots" "collect_stats"
#> [5] "colnames" "functional_enrichment" "get_anno_col" "get_anno"
#> [9] "get_classes" "get_matrix" "get_membership" "get_stats"
#> [13] "is_best_k" "is_stable_k" "ncol" "nrow"
#> [17] "rownames" "show" "suggest_best_k" "test_to_known_factors"
#> [21] "top_rows_heatmap" "top_rows_overlap"
#>
#> You can get result for a single method by, e.g. object["SD", "hclust"] or object["SD:hclust"]
#> or a subset of methods by object[c("SD", "CV")], c("hclust", "kmeans")]
The call of run_all_consensus_partition_methods() was:
#> run_all_consensus_partition_methods(data = mat, mc.cores = cores)
Dimension of the input matrix:
mat = get_matrix(res_list)
dim(mat)
#> [1] 17541 500
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 | ||
|---|---|---|---|---|---|---|
| SD:mclust | 2 | 1.000 | 0.961 | 0.977 | ** | |
| MAD:mclust | 2 | 0.980 | 0.948 | 0.969 | ** | |
| ATC:NMF | 2 | 0.939 | 0.951 | 0.979 | * | |
| ATC:skmeans | 6 | 0.914 | 0.855 | 0.940 | * | 2,4,5 |
| ATC:pam | 5 | 0.906 | 0.889 | 0.957 | * | 2,3 |
| ATC:kmeans | 2 | 0.878 | 0.949 | 0.976 | ||
| MAD:skmeans | 3 | 0.861 | 0.885 | 0.952 | ||
| SD:skmeans | 3 | 0.856 | 0.899 | 0.957 | ||
| MAD:NMF | 2 | 0.797 | 0.881 | 0.951 | ||
| CV:kmeans | 3 | 0.797 | 0.845 | 0.932 | ||
| CV:NMF | 2 | 0.781 | 0.896 | 0.950 | ||
| CV:skmeans | 3 | 0.777 | 0.832 | 0.932 | ||
| ATC:mclust | 4 | 0.696 | 0.646 | 0.843 | ||
| MAD:kmeans | 3 | 0.680 | 0.824 | 0.896 | ||
| SD:NMF | 2 | 0.673 | 0.871 | 0.935 | ||
| SD:kmeans | 3 | 0.622 | 0.812 | 0.885 | ||
| MAD:pam | 2 | 0.456 | 0.784 | 0.894 | ||
| CV:pam | 3 | 0.454 | 0.749 | 0.848 | ||
| SD:pam | 2 | 0.406 | 0.695 | 0.869 | ||
| CV:mclust | 2 | 0.346 | 0.743 | 0.855 | ||
| CV:hclust | 3 | 0.226 | 0.537 | 0.792 | ||
| ATC:hclust | 2 | 0.190 | 0.676 | 0.825 | ||
| MAD:hclust | 2 | 0.074 | 0.628 | 0.787 | ||
| SD:hclust | 2 | 0.046 | 0.484 | 0.733 |
**: 1-PAC > 0.95, *: 1-PAC > 0.9
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 0.6733 0.871 0.935 0.500 0.500 0.500
#> CV:NMF 2 0.7809 0.896 0.950 0.492 0.508 0.508
#> MAD:NMF 2 0.7975 0.881 0.951 0.498 0.502 0.502
#> ATC:NMF 2 0.9389 0.951 0.979 0.350 0.663 0.663
#> SD:skmeans 2 0.4833 0.590 0.814 0.498 0.507 0.507
#> CV:skmeans 2 0.7037 0.808 0.925 0.498 0.500 0.500
#> MAD:skmeans 2 0.8151 0.879 0.947 0.501 0.499 0.499
#> ATC:skmeans 2 0.9177 0.918 0.968 0.501 0.500 0.500
#> SD:mclust 2 1.0000 0.961 0.977 0.478 0.518 0.518
#> CV:mclust 2 0.3464 0.743 0.855 0.464 0.529 0.529
#> MAD:mclust 2 0.9797 0.948 0.969 0.480 0.521 0.521
#> ATC:mclust 2 0.8336 0.913 0.963 0.297 0.709 0.709
#> SD:kmeans 2 0.3966 0.641 0.845 0.493 0.499 0.499
#> CV:kmeans 2 0.3591 0.770 0.851 0.468 0.517 0.517
#> MAD:kmeans 2 0.4104 0.740 0.860 0.491 0.503 0.503
#> ATC:kmeans 2 0.8778 0.949 0.976 0.495 0.506 0.506
#> SD:pam 2 0.4057 0.695 0.869 0.481 0.506 0.506
#> CV:pam 2 0.2986 0.671 0.811 0.452 0.524 0.524
#> MAD:pam 2 0.4557 0.784 0.894 0.475 0.526 0.526
#> ATC:pam 2 0.9600 0.932 0.961 0.318 0.684 0.684
#> SD:hclust 2 0.0464 0.484 0.733 0.413 0.514 0.514
#> CV:hclust 2 0.3679 0.752 0.882 0.286 0.742 0.742
#> MAD:hclust 2 0.0736 0.628 0.787 0.407 0.596 0.596
#> ATC:hclust 2 0.1896 0.676 0.825 0.416 0.556 0.556
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.7234 0.808 0.910 0.326 0.694 0.463
#> CV:NMF 3 0.8029 0.820 0.928 0.321 0.767 0.574
#> MAD:NMF 3 0.5285 0.716 0.852 0.329 0.711 0.485
#> ATC:NMF 3 0.6784 0.817 0.903 0.781 0.634 0.478
#> SD:skmeans 3 0.8557 0.899 0.957 0.341 0.701 0.474
#> CV:skmeans 3 0.7774 0.832 0.932 0.307 0.756 0.552
#> MAD:skmeans 3 0.8612 0.885 0.952 0.333 0.675 0.438
#> ATC:skmeans 3 0.7983 0.849 0.921 0.305 0.737 0.527
#> SD:mclust 3 0.5643 0.710 0.837 0.202 0.965 0.933
#> CV:mclust 3 0.5722 0.730 0.845 0.383 0.747 0.551
#> MAD:mclust 3 0.6169 0.666 0.841 0.245 0.902 0.813
#> ATC:mclust 3 0.4331 0.455 0.667 0.724 0.665 0.549
#> SD:kmeans 3 0.6216 0.812 0.885 0.332 0.661 0.424
#> CV:kmeans 3 0.7967 0.845 0.932 0.324 0.781 0.612
#> MAD:kmeans 3 0.6804 0.824 0.896 0.330 0.640 0.402
#> ATC:kmeans 3 0.7772 0.831 0.933 0.234 0.626 0.415
#> SD:pam 3 0.3550 0.453 0.716 0.337 0.707 0.494
#> CV:pam 3 0.4537 0.749 0.848 0.403 0.653 0.428
#> MAD:pam 3 0.4422 0.706 0.814 0.302 0.843 0.710
#> ATC:pam 3 0.9088 0.911 0.962 0.682 0.777 0.675
#> SD:hclust 3 0.0674 0.379 0.652 0.272 0.823 0.692
#> CV:hclust 3 0.2263 0.537 0.792 0.510 0.916 0.888
#> MAD:hclust 3 0.0856 0.478 0.714 0.294 0.898 0.835
#> ATC:hclust 3 0.2228 0.506 0.656 0.387 0.664 0.478
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.536 0.593 0.787 0.0796 0.742 0.406
#> CV:NMF 4 0.637 0.715 0.827 0.1302 0.821 0.551
#> MAD:NMF 4 0.511 0.506 0.705 0.1029 0.773 0.470
#> ATC:NMF 4 0.712 0.776 0.897 0.1375 0.751 0.452
#> SD:skmeans 4 0.709 0.629 0.811 0.1166 0.845 0.582
#> CV:skmeans 4 0.772 0.797 0.908 0.1178 0.887 0.690
#> MAD:skmeans 4 0.688 0.700 0.857 0.1197 0.838 0.567
#> ATC:skmeans 4 0.925 0.911 0.962 0.1370 0.850 0.602
#> SD:mclust 4 0.543 0.592 0.767 0.1596 0.788 0.581
#> CV:mclust 4 0.561 0.508 0.728 0.1318 0.884 0.689
#> MAD:mclust 4 0.486 0.532 0.741 0.1337 0.838 0.646
#> ATC:mclust 4 0.696 0.646 0.843 0.2761 0.753 0.498
#> SD:kmeans 4 0.593 0.693 0.818 0.0938 0.818 0.550
#> CV:kmeans 4 0.647 0.683 0.816 0.1151 0.910 0.777
#> MAD:kmeans 4 0.558 0.655 0.780 0.1066 0.807 0.526
#> ATC:kmeans 4 0.657 0.781 0.889 0.1602 0.755 0.473
#> SD:pam 4 0.537 0.565 0.781 0.1330 0.814 0.539
#> CV:pam 4 0.523 0.695 0.824 0.0980 0.948 0.850
#> MAD:pam 4 0.505 0.581 0.789 0.1539 0.759 0.474
#> ATC:pam 4 0.884 0.879 0.954 0.1621 0.795 0.608
#> SD:hclust 4 0.131 0.332 0.551 0.1901 0.683 0.448
#> CV:hclust 4 0.271 0.502 0.748 0.1699 0.874 0.812
#> MAD:hclust 4 0.150 0.336 0.592 0.2165 0.767 0.586
#> ATC:hclust 4 0.305 0.462 0.694 0.1383 0.778 0.541
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.587 0.559 0.774 0.0877 0.873 0.591
#> CV:NMF 5 0.622 0.580 0.755 0.0666 0.895 0.640
#> MAD:NMF 5 0.709 0.703 0.858 0.0681 0.842 0.533
#> ATC:NMF 5 0.694 0.703 0.854 0.0944 0.777 0.390
#> SD:skmeans 5 0.662 0.568 0.764 0.0630 0.874 0.568
#> CV:skmeans 5 0.696 0.644 0.814 0.0662 0.942 0.798
#> MAD:skmeans 5 0.652 0.323 0.655 0.0653 0.865 0.544
#> ATC:skmeans 5 0.930 0.879 0.946 0.0524 0.908 0.674
#> SD:mclust 5 0.559 0.599 0.742 0.1161 0.840 0.559
#> CV:mclust 5 0.527 0.367 0.676 0.0413 0.881 0.643
#> MAD:mclust 5 0.496 0.367 0.670 0.0830 0.884 0.681
#> ATC:mclust 5 0.734 0.822 0.905 0.0414 0.865 0.643
#> SD:kmeans 5 0.642 0.641 0.777 0.0677 0.901 0.686
#> CV:kmeans 5 0.608 0.620 0.774 0.0709 0.951 0.853
#> MAD:kmeans 5 0.623 0.576 0.757 0.0701 0.920 0.739
#> ATC:kmeans 5 0.875 0.851 0.939 0.0798 0.866 0.592
#> SD:pam 5 0.546 0.491 0.696 0.0626 0.833 0.492
#> CV:pam 5 0.558 0.601 0.778 0.0710 0.953 0.849
#> MAD:pam 5 0.634 0.582 0.791 0.0707 0.897 0.670
#> ATC:pam 5 0.906 0.889 0.957 0.1245 0.900 0.743
#> SD:hclust 5 0.214 0.341 0.564 0.1015 0.814 0.562
#> CV:hclust 5 0.283 0.456 0.733 0.1154 0.940 0.893
#> MAD:hclust 5 0.238 0.329 0.566 0.1060 0.840 0.606
#> ATC:hclust 5 0.394 0.495 0.683 0.0848 0.842 0.598
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.660 0.531 0.759 0.0384 0.885 0.565
#> CV:NMF 6 0.656 0.504 0.735 0.0398 0.850 0.469
#> MAD:NMF 6 0.734 0.667 0.809 0.0431 0.925 0.692
#> ATC:NMF 6 0.643 0.558 0.755 0.0545 0.895 0.587
#> SD:skmeans 6 0.740 0.629 0.815 0.0425 0.886 0.535
#> CV:skmeans 6 0.708 0.465 0.740 0.0505 0.898 0.619
#> MAD:skmeans 6 0.722 0.577 0.777 0.0418 0.850 0.426
#> ATC:skmeans 6 0.914 0.855 0.940 0.0423 0.938 0.730
#> SD:mclust 6 0.593 0.559 0.703 0.0569 0.941 0.790
#> CV:mclust 6 0.538 0.334 0.622 0.0487 0.883 0.603
#> MAD:mclust 6 0.559 0.347 0.681 0.0730 0.799 0.423
#> ATC:mclust 6 0.788 0.823 0.904 0.0940 0.862 0.610
#> SD:kmeans 6 0.682 0.624 0.745 0.0531 0.894 0.601
#> CV:kmeans 6 0.618 0.505 0.697 0.0569 0.909 0.713
#> MAD:kmeans 6 0.643 0.506 0.702 0.0478 0.853 0.501
#> ATC:kmeans 6 0.717 0.607 0.794 0.0549 0.943 0.773
#> SD:pam 6 0.615 0.562 0.734 0.0451 0.870 0.522
#> CV:pam 6 0.597 0.550 0.717 0.0657 0.865 0.554
#> MAD:pam 6 0.609 0.440 0.694 0.0429 0.855 0.532
#> ATC:pam 6 0.810 0.822 0.924 0.0939 0.910 0.710
#> SD:hclust 6 0.298 0.395 0.565 0.0769 0.877 0.619
#> CV:hclust 6 0.304 0.466 0.698 0.0866 0.919 0.845
#> MAD:hclust 6 0.318 0.362 0.583 0.0654 0.865 0.605
#> ATC:hclust 6 0.459 0.491 0.689 0.0454 0.920 0.743
Following heatmap plots the partition for each combination of methods and the lightness correspond to the silhouette scores for samples in each method. On top the consensus subgroup is inferred from all methods by taking the mean silhouette scores as weight.
collect_stats(res_list, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.0464 0.484 0.733 0.4127 0.514 0.514
#> 3 3 0.0674 0.379 0.652 0.2722 0.823 0.692
#> 4 4 0.1312 0.332 0.551 0.1901 0.683 0.448
#> 5 5 0.2142 0.341 0.564 0.1015 0.814 0.562
#> 6 6 0.2977 0.395 0.565 0.0769 0.877 0.619
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.9129 0.40639 0.328 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2043 0.61573 0.968 0.032
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.4022 0.64291 0.080 0.920
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.9977 0.14408 0.528 0.472
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.9732 0.37911 0.596 0.404
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.6712 0.65516 0.176 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9996 0.02244 0.488 0.512
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.9993 0.06515 0.516 0.484
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.7883 0.61082 0.236 0.764
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.7950 0.57125 0.240 0.760
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.7674 0.60425 0.224 0.776
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.9963 0.16297 0.464 0.536
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.9286 0.45580 0.344 0.656
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.9993 0.12755 0.484 0.516
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.7299 0.65604 0.796 0.204
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.9522 0.45000 0.372 0.628
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.2043 0.61573 0.968 0.032
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.9170 0.48382 0.332 0.668
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.9686 0.40311 0.604 0.396
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.3431 0.63286 0.064 0.936
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#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.3584 0.63769 0.068 0.932
#> 80936433-AA91-4219-98F1-706C36298060 2 0.4562 0.64421 0.096 0.904
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.2043 0.61573 0.968 0.032
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.9909 0.27188 0.444 0.556
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.9833 0.31519 0.576 0.424
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.2778 0.60449 0.952 0.048
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.6148 0.51750 0.152 0.848
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 2 0.9896 0.26501 0.440 0.560
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.5178 0.65921 0.884 0.116
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.7602 0.65043 0.780 0.220
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.8608 0.60708 0.716 0.284
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.9686 0.40418 0.604 0.396
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.6343 0.65051 0.160 0.840
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.7883 0.61082 0.236 0.764
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.2043 0.61573 0.968 0.032
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.6712 0.66422 0.824 0.176
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.2423 0.60123 0.960 0.040
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.9635 0.37143 0.388 0.612
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.7139 0.66106 0.804 0.196
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 2 0.8608 0.58285 0.284 0.716
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.7139 0.64639 0.196 0.804
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.5946 0.66590 0.856 0.144
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 2 0.8763 0.56356 0.296 0.704
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.9909 0.27188 0.444 0.556
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.6531 0.66428 0.832 0.168
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.9170 0.54228 0.668 0.332
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.8608 0.61021 0.716 0.284
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.5178 0.65432 0.116 0.884
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.8813 0.54146 0.300 0.700
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.8555 0.61025 0.720 0.280
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.9710 0.34241 0.400 0.600
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.7602 0.64161 0.220 0.780
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.7528 0.62734 0.216 0.784
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.2423 0.60123 0.960 0.040
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.9710 0.31573 0.400 0.600
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.2043 0.61573 0.968 0.032
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.8081 0.63765 0.752 0.248
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.8386 0.60942 0.268 0.732
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.3114 0.62547 0.056 0.944
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.9815 0.36347 0.580 0.420
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.9732 0.36893 0.596 0.404
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 2 0.6247 0.65183 0.156 0.844
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 2 0.9909 0.24729 0.444 0.556
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.5946 0.66511 0.856 0.144
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.8386 0.57659 0.268 0.732
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.8443 0.56942 0.272 0.728
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2043 0.61573 0.968 0.032
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.6438 0.65267 0.164 0.836
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 1.0000 0.03666 0.504 0.496
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.9427 0.50890 0.360 0.640
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.6247 0.65190 0.156 0.844
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.9608 0.45194 0.384 0.616
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.7453 0.64323 0.212 0.788
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.6247 0.65030 0.156 0.844
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 2 0.9661 0.40336 0.392 0.608
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.9833 0.31519 0.576 0.424
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.9963 0.14708 0.536 0.464
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.9209 0.53631 0.664 0.336
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.9983 0.12431 0.524 0.476
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.9686 0.39595 0.396 0.604
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.2603 0.63262 0.044 0.956
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.8763 0.58946 0.704 0.296
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.7219 0.60427 0.200 0.800
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.7883 0.61041 0.236 0.764
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.5178 0.65921 0.884 0.116
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.9393 0.48292 0.356 0.644
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.5178 0.65612 0.116 0.884
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.6343 0.66629 0.840 0.160
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 2 0.9754 0.37168 0.408 0.592
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.6712 0.63026 0.824 0.176
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.2948 0.63077 0.948 0.052
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.2948 0.63077 0.948 0.052
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4939 0.65676 0.892 0.108
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9909 0.26784 0.556 0.444
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.6148 0.66323 0.848 0.152
#> C33059A9-A313-4806-B43B-0031365F3BE4 2 1.0000 0.05770 0.496 0.504
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.8443 0.59230 0.272 0.728
#> 1122039D-5785-4F70-9916-17C585453512 1 0.4690 0.61768 0.900 0.100
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6801 0.57765 0.820 0.180
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.9580 0.47608 0.380 0.620
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 1.0000 0.01040 0.496 0.504
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.9732 0.36175 0.404 0.596
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.9427 0.44926 0.360 0.640
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.9983 0.07366 0.524 0.476
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.4690 0.61768 0.900 0.100
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.9993 0.08274 0.516 0.484
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.9996 0.03371 0.512 0.488
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.3114 0.63807 0.056 0.944
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.9732 0.40015 0.596 0.404
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.9358 0.51482 0.648 0.352
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.5737 0.66347 0.864 0.136
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.9996 0.09344 0.512 0.488
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.4939 0.65501 0.108 0.892
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.9970 0.14228 0.532 0.468
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.9522 0.47840 0.372 0.628
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.6438 0.65703 0.164 0.836
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.9881 0.30964 0.564 0.436
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 2 0.9996 0.06374 0.488 0.512
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 2 0.9933 0.21768 0.452 0.548
#> EB7883EB-0079-4548-9132-169E94A698BA 2 0.9944 0.19721 0.456 0.544
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.9209 0.53115 0.664 0.336
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.2043 0.61573 0.968 0.032
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.8661 0.59926 0.712 0.288
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.3431 0.63904 0.064 0.936
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.2236 0.60439 0.036 0.964
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.6343 0.62787 0.160 0.840
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.9833 0.31519 0.576 0.424
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.9954 0.19263 0.460 0.540
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 2 0.9833 0.31107 0.424 0.576
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.7815 0.64489 0.768 0.232
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3481 0.62224 0.044 0.904 0.052
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0747 0.58636 0.984 0.016 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3445 0.45974 0.016 0.088 0.896
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.7069 0.09961 0.508 0.020 0.472
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.9208 0.33958 0.532 0.204 0.264
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.5263 0.57742 0.116 0.060 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.9018 0.04120 0.456 0.132 0.412
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.6468 0.14282 0.444 0.004 0.552
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.4164 0.57196 0.144 0.008 0.848
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.7777 -0.15581 0.060 0.364 0.576
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.8876 0.33413 0.120 0.468 0.412
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.6451 0.29753 0.384 0.008 0.608
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 3 0.9815 0.23456 0.324 0.256 0.420
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.6836 0.27786 0.412 0.016 0.572
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5331 0.61019 0.792 0.024 0.184
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.6255 0.46412 0.300 0.016 0.684
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0747 0.58636 0.984 0.016 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 3 0.9805 -0.00792 0.256 0.320 0.424
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.9147 0.35581 0.540 0.200 0.260
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 3 0.7699 -0.18691 0.048 0.420 0.532
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.6897 0.62436 0.068 0.712 0.220
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 3 0.9645 0.13711 0.380 0.208 0.412
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.6229 0.53267 0.764 0.172 0.064
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 3 0.7152 -0.23917 0.024 0.444 0.532
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.2496 0.61959 0.928 0.004 0.068
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 3 0.7236 -0.09510 0.032 0.392 0.576
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.6449 0.57522 0.204 0.056 0.740
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6822 0.02591 0.508 0.012 0.480
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.5835 0.47023 0.660 0.000 0.340
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.7075 -0.06352 0.484 0.020 0.496
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.5760 0.41468 0.328 0.000 0.672
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 3 0.7699 -0.18691 0.048 0.420 0.532
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.2056 0.59791 0.952 0.024 0.024
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.6451 0.30595 0.384 0.008 0.608
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.8207 0.48459 0.216 0.148 0.636
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.5526 0.60295 0.792 0.036 0.172
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5610 0.60460 0.776 0.028 0.196
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.5502 0.51826 0.248 0.008 0.744
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1878 0.61104 0.952 0.004 0.044
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.1585 0.58526 0.964 0.028 0.008
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.6608 0.17691 0.432 0.008 0.560
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.7169 0.32067 0.568 0.028 0.404
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 1 0.9243 0.15142 0.492 0.168 0.340
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.7584 0.46130 0.676 0.220 0.104
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.5470 0.60643 0.796 0.036 0.168
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4966 0.50008 0.060 0.100 0.840
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.6897 0.62436 0.068 0.712 0.220
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.6925 0.15100 0.452 0.016 0.532
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.8543 0.40552 0.268 0.140 0.592
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.9847 0.06793 0.416 0.268 0.316
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.6095 0.30121 0.392 0.000 0.608
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.6498 0.25728 0.396 0.008 0.596
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.9736 0.39475 0.240 0.436 0.324
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.6322 0.56905 0.120 0.108 0.772
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.3686 0.62530 0.860 0.000 0.140
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.6079 0.60333 0.748 0.036 0.216
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 3 0.9724 0.18698 0.364 0.224 0.412
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.5741 0.59241 0.776 0.036 0.188
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.4810 0.59152 0.140 0.028 0.832
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.9633 0.00972 0.424 0.208 0.368
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.6008 0.42799 0.628 0.000 0.372
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.7620 0.38836 0.596 0.056 0.348
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3715 0.62856 0.868 0.004 0.128
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.6577 0.30685 0.572 0.008 0.420
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.6553 0.42327 0.324 0.020 0.656
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.5428 0.49125 0.064 0.120 0.816
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3683 0.62304 0.044 0.896 0.060
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.7032 0.43298 0.604 0.028 0.368
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#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.6096 0.54540 0.704 0.016 0.280
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.6291 0.46908 0.080 0.152 0.768
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.8600 0.40924 0.284 0.136 0.580
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.6200 0.51167 0.676 0.012 0.312
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.9234 0.23200 0.364 0.160 0.476
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.4270 0.59156 0.116 0.024 0.860
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.4349 0.58222 0.128 0.020 0.852
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.6897 0.45243 0.712 0.220 0.068
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.9792 0.15174 0.372 0.236 0.392
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0747 0.58636 0.984 0.016 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.5529 0.54020 0.704 0.000 0.296
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.5521 0.57798 0.180 0.032 0.788
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 3 0.7480 -0.26417 0.036 0.456 0.508
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.7378 0.29822 0.560 0.036 0.404
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.6291 0.16242 0.532 0.000 0.468
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4505 0.55766 0.092 0.048 0.860
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.6777 0.34455 0.364 0.020 0.616
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.3412 0.62858 0.876 0.000 0.124
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 3 0.8779 0.43602 0.248 0.172 0.580
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 3 0.9574 0.34258 0.244 0.276 0.480
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0747 0.58636 0.984 0.016 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4369 0.56552 0.096 0.040 0.864
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.6260 0.15049 0.448 0.000 0.552
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.8419 0.48046 0.212 0.168 0.620
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4174 0.56242 0.092 0.036 0.872
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.8375 0.45603 0.260 0.132 0.608
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.4563 0.58202 0.112 0.036 0.852
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4121 0.55136 0.084 0.040 0.876
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.5621 0.44883 0.308 0.000 0.692
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.6680 0.12378 0.508 0.008 0.484
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.6500 0.07850 0.464 0.004 0.532
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.7815 0.48599 0.644 0.096 0.260
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.7072 0.08464 0.504 0.020 0.476
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.6396 0.43872 0.320 0.016 0.664
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4291 0.39330 0.008 0.152 0.840
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.6104 0.46145 0.648 0.004 0.348
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.8527 0.41068 0.096 0.504 0.400
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 3 0.8271 0.48960 0.212 0.156 0.632
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3192 0.62604 0.888 0.000 0.112
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.5692 0.49607 0.268 0.008 0.724
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3998 0.52467 0.056 0.060 0.884
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.4062 0.62292 0.836 0.000 0.164
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.6205 0.41600 0.336 0.008 0.656
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.7999 0.54033 0.656 0.196 0.148
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1015 0.59697 0.980 0.008 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.1015 0.59697 0.980 0.008 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.2959 0.62418 0.900 0.000 0.100
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9513 0.27672 0.492 0.256 0.252
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.3752 0.62486 0.856 0.000 0.144
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.6274 0.15920 0.456 0.000 0.544
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.5277 0.57028 0.180 0.024 0.796
#> 1122039D-5785-4F70-9916-17C585453512 1 0.3583 0.57107 0.900 0.044 0.056
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.9092 0.39051 0.548 0.200 0.252
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.8336 0.47072 0.224 0.152 0.624
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.9606 0.04879 0.472 0.240 0.288
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.9910 0.18490 0.292 0.308 0.400
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.8882 0.34817 0.316 0.144 0.540
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.6521 -0.02832 0.500 0.004 0.496
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.3583 0.57107 0.900 0.044 0.056
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.6460 0.15329 0.440 0.004 0.556
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.6267 0.15060 0.452 0.000 0.548
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3845 0.43881 0.012 0.116 0.872
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.6905 0.26463 0.544 0.016 0.440
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.7301 0.45823 0.640 0.052 0.308
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.3412 0.62725 0.876 0.000 0.124
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.9758 0.14503 0.440 0.256 0.304
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3993 0.51691 0.052 0.064 0.884
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.6664 0.04627 0.464 0.008 0.528
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.8210 0.47318 0.240 0.132 0.628
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.6254 0.56528 0.116 0.108 0.776
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.9153 0.29576 0.524 0.176 0.300
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.6410 0.22238 0.420 0.004 0.576
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.6814 0.32697 0.372 0.020 0.608
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.6095 0.29609 0.392 0.000 0.608
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.6079 0.38753 0.612 0.000 0.388
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0747 0.58636 0.984 0.016 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.5982 0.48959 0.668 0.004 0.328
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6678 0.33445 0.060 0.216 0.724
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.5938 0.14978 0.020 0.248 0.732
#> A0C429D9-0638-4873-BFB4-00056AB4719F 3 0.8777 0.07293 0.148 0.288 0.564
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.6680 0.12378 0.508 0.008 0.484
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.7868 0.22984 0.420 0.056 0.524
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5948 0.37232 0.360 0.000 0.640
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5291 0.56248 0.732 0.000 0.268
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.606 0.703576 0.084 0.240 0.004 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.355 0.631908 0.856 0.008 0.120 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.615 0.202170 0.008 0.488 0.472 0.032
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.764 0.114178 0.356 0.184 0.456 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.868 0.282580 0.408 0.256 0.296 0.040
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.607 0.211313 0.016 0.288 0.652 0.044
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.831 0.035327 0.300 0.284 0.400 0.016
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.380 0.496940 0.148 0.012 0.832 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.527 0.306509 0.024 0.268 0.700 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.888 0.237275 0.068 0.440 0.272 0.220
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.831 0.299139 0.084 0.556 0.188 0.172
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.432 0.537814 0.120 0.048 0.824 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.913 0.276580 0.200 0.400 0.312 0.088
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.497 0.535613 0.136 0.080 0.780 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.614 0.517895 0.584 0.060 0.356 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.499 0.521414 0.072 0.148 0.776 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.355 0.631908 0.856 0.008 0.120 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.901 0.338122 0.196 0.472 0.224 0.108
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.869 0.299119 0.404 0.252 0.304 0.040
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.683 0.424306 0.012 0.640 0.184 0.164
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.622 0.698110 0.072 0.212 0.024 0.692
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.889 0.121852 0.244 0.352 0.352 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.751 0.478942 0.596 0.032 0.208 0.164
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.693 0.400556 0.008 0.620 0.180 0.192
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.416 0.631366 0.772 0.004 0.220 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.669 0.467115 0.004 0.632 0.212 0.152
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.680 0.301075 0.068 0.292 0.612 0.028
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.533 0.422721 0.236 0.044 0.716 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.562 0.077619 0.372 0.012 0.604 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.547 0.432867 0.236 0.028 0.716 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.455 0.529761 0.100 0.096 0.804 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.683 0.424306 0.012 0.640 0.184 0.164
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.395 0.634859 0.832 0.012 0.140 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.371 0.549571 0.100 0.040 0.856 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.675 0.328437 0.064 0.188 0.680 0.068
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.633 0.519421 0.592 0.080 0.328 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.624 0.487040 0.568 0.064 0.368 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.560 0.433428 0.076 0.200 0.720 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.389 0.634276 0.796 0.000 0.196 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.378 0.626892 0.852 0.012 0.112 0.024
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.377 0.508095 0.136 0.016 0.840 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.637 0.245489 0.308 0.068 0.616 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 3 0.861 -0.063653 0.296 0.280 0.392 0.032
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.825 0.344177 0.516 0.044 0.240 0.200
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.637 0.522299 0.584 0.080 0.336 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.628 -0.094175 0.004 0.428 0.520 0.048
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.622 0.698110 0.072 0.212 0.024 0.692
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.635 0.436079 0.244 0.116 0.640 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.856 0.243213 0.180 0.200 0.528 0.092
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.917 0.011155 0.308 0.328 0.296 0.068
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.348 0.544909 0.116 0.028 0.856 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.565 0.535869 0.168 0.100 0.728 0.004
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.954 0.271560 0.204 0.288 0.136 0.372
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.635 0.236911 0.016 0.256 0.656 0.072
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.480 0.554034 0.656 0.000 0.340 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.633 0.422149 0.536 0.028 0.416 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.876 0.122603 0.220 0.380 0.352 0.048
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.652 0.495829 0.576 0.092 0.332 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.592 0.280133 0.024 0.272 0.672 0.032
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.917 0.055146 0.288 0.324 0.320 0.068
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.545 0.168927 0.332 0.012 0.644 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.787 0.247294 0.440 0.204 0.348 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.479 0.585788 0.680 0.008 0.312 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.512 0.287651 0.276 0.016 0.700 0.008
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.516 0.541073 0.100 0.116 0.776 0.008
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.663 -0.100516 0.004 0.412 0.512 0.072
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.643 0.699870 0.084 0.256 0.012 0.648
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.609 0.113337 0.340 0.032 0.612 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.556 0.429574 0.236 0.056 0.704 0.004
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.453 0.602064 0.704 0.000 0.292 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 1 0.950 -0.012046 0.396 0.264 0.144 0.196
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.986 0.224195 0.292 0.176 0.236 0.296
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.822 0.248201 0.236 0.408 0.340 0.016
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.679 0.702595 0.072 0.264 0.032 0.632
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.750 -0.219509 0.004 0.372 0.464 0.160
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.378 0.626892 0.852 0.012 0.112 0.024
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.579 -0.042777 0.004 0.416 0.556 0.024
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.613 0.466228 0.104 0.184 0.700 0.012
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.598 0.060587 0.024 0.392 0.572 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.639 0.241241 0.000 0.488 0.448 0.064
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.640 0.185686 0.328 0.064 0.600 0.008
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.675 0.381438 0.016 0.656 0.164 0.164
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#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.479 0.585788 0.680 0.008 0.312 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.549 0.446606 0.076 0.188 0.732 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.616 0.495640 0.104 0.132 0.728 0.036
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.503 0.472709 0.596 0.004 0.400 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.753 0.341388 0.460 0.164 0.372 0.004
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.624 0.316463 0.504 0.044 0.448 0.004
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.716 0.316433 0.060 0.496 0.412 0.032
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.814 0.261035 0.216 0.420 0.348 0.016
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.586 0.009149 0.384 0.020 0.584 0.012
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.827 0.025774 0.224 0.348 0.408 0.020
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.498 0.297069 0.004 0.260 0.716 0.020
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.571 0.234953 0.024 0.300 0.660 0.016
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.783 0.346949 0.576 0.044 0.180 0.200
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.885 -0.102437 0.228 0.356 0.364 0.052
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.355 0.631908 0.856 0.008 0.120 0.016
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.566 -0.131017 0.436 0.008 0.544 0.012
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.605 0.342644 0.056 0.268 0.664 0.012
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.655 0.393140 0.008 0.660 0.156 0.176
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 3 0.758 -0.018954 0.364 0.156 0.472 0.008
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.524 0.380870 0.264 0.024 0.704 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.572 0.118358 0.016 0.372 0.600 0.012
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.416 0.552952 0.108 0.056 0.832 0.004
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.454 0.582916 0.676 0.000 0.324 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.807 0.267638 0.168 0.440 0.368 0.024
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.882 0.361833 0.148 0.440 0.324 0.088
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.355 0.631908 0.856 0.008 0.120 0.016
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.588 0.132367 0.024 0.360 0.604 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.568 0.494145 0.208 0.068 0.716 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.674 0.313877 0.060 0.188 0.680 0.072
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.558 0.136251 0.016 0.364 0.612 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.608 0.407584 0.052 0.164 0.728 0.056
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.573 0.207043 0.012 0.308 0.652 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.597 0.050903 0.016 0.384 0.580 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.448 0.528965 0.084 0.096 0.816 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.465 0.405156 0.216 0.016 0.760 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.387 0.478500 0.164 0.008 0.820 0.008
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.773 0.345945 0.460 0.160 0.368 0.012
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.766 0.114472 0.352 0.188 0.456 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.470 0.533848 0.076 0.120 0.800 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.680 -0.235135 0.000 0.448 0.456 0.096
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.554 0.108038 0.352 0.012 0.624 0.012
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.783 0.239618 0.076 0.604 0.148 0.172
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.766 0.270982 0.136 0.460 0.388 0.016
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.443 0.590015 0.696 0.000 0.304 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.535 0.499304 0.080 0.136 0.768 0.016
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.587 0.038221 0.004 0.380 0.584 0.032
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.476 0.531396 0.628 0.000 0.372 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.551 0.545427 0.128 0.124 0.744 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.840 0.496573 0.552 0.108 0.204 0.136
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.371 0.635935 0.832 0.004 0.152 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.371 0.635935 0.832 0.004 0.152 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.451 0.603124 0.708 0.000 0.288 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.912 0.207364 0.368 0.272 0.292 0.068
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.460 0.566571 0.664 0.000 0.336 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.521 0.478998 0.224 0.052 0.724 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.476 0.367359 0.020 0.216 0.756 0.008
#> 1122039D-5785-4F70-9916-17C585453512 1 0.485 0.580313 0.812 0.032 0.096 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.879 0.203406 0.392 0.060 0.360 0.188
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.647 0.340158 0.056 0.188 0.696 0.060
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.950 -0.012046 0.396 0.264 0.144 0.196
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.923 -0.252523 0.196 0.348 0.360 0.096
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.808 -0.005544 0.200 0.360 0.424 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.579 0.369686 0.284 0.060 0.656 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.485 0.580313 0.812 0.032 0.096 0.060
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.591 0.523990 0.192 0.092 0.708 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.418 0.502585 0.160 0.020 0.812 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.644 -0.169465 0.000 0.436 0.496 0.068
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.657 0.291092 0.300 0.084 0.608 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.748 0.291163 0.456 0.156 0.384 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.445 0.593336 0.692 0.000 0.308 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.917 0.055644 0.332 0.308 0.292 0.068
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.591 0.003509 0.004 0.392 0.572 0.032
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.425 0.464773 0.176 0.016 0.800 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.624 0.380202 0.056 0.172 0.716 0.056
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.643 0.209978 0.016 0.268 0.644 0.072
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.860 0.214935 0.396 0.272 0.300 0.032
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.354 0.522749 0.128 0.012 0.852 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.420 0.555542 0.112 0.048 0.832 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.327 0.542231 0.108 0.024 0.868 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.539 0.195388 0.320 0.012 0.656 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.355 0.631908 0.856 0.008 0.120 0.016
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.563 0.051287 0.376 0.012 0.600 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.717 0.449913 0.040 0.564 0.332 0.064
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.809 0.379032 0.020 0.472 0.296 0.212
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.781 0.494362 0.104 0.588 0.232 0.076
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.465 0.405156 0.216 0.016 0.760 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.617 0.500182 0.160 0.148 0.688 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.502 0.536018 0.144 0.088 0.768 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.581 -0.209613 0.460 0.012 0.516 0.012
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.696 0.679605 0.000 0.380 0.092 0.064 0.464
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.475 0.604229 0.260 0.044 0.692 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.838 0.115639 0.368 0.152 0.160 0.312 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.734 0.143782 0.240 0.420 0.024 0.312 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.541 -0.243300 0.496 0.016 0.460 0.000 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.869 -0.199811 0.340 0.280 0.176 0.192 0.012
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.242 0.551037 0.908 0.008 0.052 0.032 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.475 -0.106852 0.556 0.012 0.428 0.004 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.776 0.227007 0.124 0.204 0.548 0.040 0.084
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.541 0.348656 0.096 0.744 0.104 0.044 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.315 0.539658 0.860 0.012 0.104 0.024 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.771 0.507675 0.216 0.520 0.100 0.152 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.521 0.534941 0.748 0.076 0.100 0.076 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.613 0.417418 0.384 0.104 0.008 0.504 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.501 0.419163 0.708 0.044 0.224 0.024 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.711 0.416791 0.112 0.604 0.128 0.144 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.754 0.126251 0.240 0.412 0.024 0.312 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.520 0.376286 0.048 0.696 0.232 0.004 0.020
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 5 0.370 0.706486 0.000 0.040 0.092 0.028 0.840
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.829 0.432559 0.248 0.424 0.152 0.168 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.805 0.450648 0.284 0.108 0.084 0.480 0.044
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.686 0.285504 0.048 0.536 0.304 0.004 0.108
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.389 0.629324 0.240 0.004 0.004 0.748 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.631 0.313526 0.060 0.556 0.332 0.000 0.052
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.620 -0.046917 0.504 0.024 0.416 0.036 0.020
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.548 0.539890 0.712 0.052 0.072 0.164 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.430 0.359925 0.736 0.008 0.024 0.232 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.474 0.557642 0.772 0.020 0.084 0.120 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.510 0.446862 0.708 0.016 0.208 0.068 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.520 0.376286 0.048 0.696 0.232 0.004 0.020
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.325 0.590374 0.084 0.040 0.008 0.864 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.432 0.526952 0.792 0.024 0.132 0.052 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.676 0.243086 0.600 0.156 0.196 0.036 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.649 0.413977 0.344 0.156 0.008 0.492 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 4 0.637 0.368866 0.408 0.116 0.012 0.464 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.518 0.183162 0.600 0.004 0.352 0.044 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.337 0.637232 0.212 0.000 0.000 0.784 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.271 0.588114 0.076 0.004 0.008 0.892 0.020
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.254 0.548647 0.904 0.016 0.056 0.024 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.587 0.438786 0.668 0.056 0.072 0.204 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.813 0.257317 0.344 0.352 0.100 0.200 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.865 0.321780 0.300 0.140 0.104 0.404 0.052
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.655 0.419460 0.356 0.148 0.012 0.484 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.500 0.567714 0.304 0.016 0.656 0.004 0.020
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 5 0.370 0.706486 0.000 0.040 0.092 0.028 0.840
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.714 0.443528 0.548 0.072 0.172 0.208 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.795 0.062806 0.464 0.088 0.292 0.136 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.707 0.373537 0.224 0.524 0.020 0.220 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.429 0.524440 0.788 0.012 0.132 0.068 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.541 0.521723 0.684 0.012 0.200 0.104 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 5 0.890 0.247336 0.072 0.276 0.088 0.176 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.559 -0.139799 0.512 0.016 0.432 0.000 0.040
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.449 0.501700 0.404 0.000 0.004 0.588 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.569 -0.191017 0.528 0.044 0.012 0.412 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.841 0.407917 0.284 0.412 0.156 0.128 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 4 0.675 0.367188 0.336 0.184 0.012 0.468 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.512 -0.107379 0.548 0.040 0.412 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.776 0.389413 0.228 0.464 0.076 0.228 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.433 0.414941 0.756 0.012 0.032 0.200 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 4 0.846 -0.002801 0.272 0.236 0.112 0.368 0.012
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 4 0.473 0.516641 0.396 0.008 0.004 0.588 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.415 0.487004 0.804 0.016 0.044 0.132 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.562 0.465484 0.680 0.044 0.212 0.064 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.544 0.561036 0.312 0.020 0.628 0.004 0.036
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.722 0.665209 0.004 0.392 0.104 0.064 0.436
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.530 0.372549 0.720 0.048 0.044 0.184 0.004
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#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.475 -0.106852 0.556 0.012 0.428 0.004 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.703 0.243523 0.568 0.132 0.088 0.212 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 1 0.822 -0.143619 0.380 0.284 0.108 0.224 0.004
#> E789661A-C027-405D-9F76-E6D52CE3018B 1 0.820 -0.185037 0.340 0.272 0.060 0.312 0.016
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.696 0.405857 0.328 0.164 0.012 0.484 0.012
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.755 0.308806 0.220 0.240 0.488 0.028 0.024
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 4 0.438 0.551172 0.364 0.000 0.004 0.628 0.004
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.340 0.636461 0.216 0.000 0.000 0.780 0.004
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.466 0.560767 0.784 0.044 0.080 0.092 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.582 -0.060738 0.556 0.072 0.012 0.360 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.461 0.609222 0.224 0.016 0.728 0.000 0.032
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 4 0.835 0.059154 0.284 0.216 0.104 0.384 0.012
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 5 0.860 0.583624 0.040 0.336 0.120 0.132 0.372
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 3 0.711 0.197841 0.128 0.304 0.520 0.020 0.028
#> 80936433-AA91-4219-98F1-706C36298060 3 0.790 0.089567 0.124 0.296 0.472 0.024 0.084
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.581 0.486313 0.700 0.160 0.084 0.048 0.008
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.362 0.552801 0.848 0.016 0.048 0.084 0.004
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.860 0.330735 0.288 0.136 0.104 0.420 0.052
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 5 0.458 0.698789 0.000 0.220 0.016 0.032 0.732
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.352 0.525284 0.828 0.008 0.136 0.028 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.436 0.555405 0.360 0.000 0.004 0.632 0.004
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.585 0.089816 0.612 0.036 0.036 0.308 0.008
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.551 0.190985 0.636 0.072 0.012 0.280 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.465 0.501240 0.740 0.012 0.052 0.196 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.510 0.430343 0.428 0.016 0.544 0.008 0.004
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.475 -0.106852 0.556 0.012 0.428 0.004 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.636 0.517479 0.336 0.104 0.016 0.540 0.004
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.845 0.340319 0.244 0.140 0.100 0.464 0.052
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.869 0.290190 0.312 0.316 0.232 0.120 0.020
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.504 0.390820 0.452 0.008 0.012 0.524 0.004
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.481 0.223849 0.636 0.016 0.336 0.012 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.479 -0.214885 0.520 0.012 0.464 0.000 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.473 0.516641 0.396 0.008 0.004 0.588 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.545 0.258944 0.624 0.028 0.312 0.036 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.581 0.486313 0.700 0.160 0.084 0.048 0.008
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.471 0.341388 0.484 0.000 0.008 0.504 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.786 -0.227305 0.352 0.256 0.040 0.340 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.646 -0.156011 0.464 0.068 0.044 0.424 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.704 0.400534 0.192 0.216 0.552 0.020 0.020
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.863 -0.161713 0.180 0.292 0.348 0.168 0.012
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.457 0.295428 0.708 0.012 0.024 0.256 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.873 0.284447 0.308 0.316 0.228 0.128 0.020
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.486 -0.092765 0.548 0.024 0.428 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.512 -0.253397 0.500 0.028 0.468 0.000 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.845 0.340319 0.244 0.140 0.100 0.464 0.052
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.827 0.410927 0.300 0.420 0.112 0.148 0.020
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.481 0.139854 0.640 0.004 0.020 0.332 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.595 -0.032593 0.528 0.052 0.392 0.028 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.537 0.332212 0.028 0.668 0.256 0.000 0.048
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.803 -0.013382 0.392 0.204 0.108 0.296 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.473 0.517465 0.732 0.004 0.076 0.188 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.520 0.449601 0.416 0.016 0.552 0.008 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.492 0.510975 0.744 0.024 0.160 0.072 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.456 0.543298 0.376 0.004 0.004 0.612 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.848 0.232513 0.220 0.356 0.304 0.104 0.016
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.825 0.456622 0.216 0.476 0.180 0.096 0.032
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.521 0.414529 0.436 0.016 0.532 0.012 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.573 0.534990 0.676 0.024 0.140 0.160 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.699 0.227060 0.588 0.176 0.180 0.036 0.020
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.510 0.438101 0.424 0.016 0.548 0.008 0.004
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.616 0.358496 0.660 0.152 0.148 0.032 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.517 -0.255432 0.500 0.040 0.460 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.494 0.495224 0.392 0.024 0.580 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.500 0.433938 0.716 0.020 0.208 0.056 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.362 0.552801 0.848 0.016 0.048 0.084 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.251 0.555334 0.904 0.008 0.040 0.048 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.789 -0.226144 0.352 0.260 0.036 0.336 0.016
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.841 0.112055 0.364 0.156 0.160 0.312 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.485 0.453895 0.736 0.044 0.192 0.028 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.509 0.596393 0.252 0.016 0.684 0.000 0.048
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.453 0.359057 0.736 0.008 0.032 0.220 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.501 0.283706 0.048 0.772 0.120 0.040 0.020
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 3 0.833 -0.031913 0.224 0.288 0.384 0.088 0.016
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.436 0.555405 0.360 0.000 0.004 0.632 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.405 0.395724 0.744 0.012 0.236 0.008 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.487 0.489419 0.384 0.012 0.592 0.000 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.488 0.478222 0.416 0.004 0.012 0.564 0.004
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.554 0.482045 0.684 0.032 0.208 0.076 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.801 0.304293 0.212 0.228 0.072 0.468 0.020
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.260 0.632555 0.148 0.000 0.000 0.852 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.260 0.632555 0.148 0.000 0.000 0.852 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.422 0.587438 0.324 0.000 0.004 0.668 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.740 0.238025 0.224 0.464 0.016 0.276 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.461 0.503220 0.408 0.000 0.008 0.580 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.605 0.503786 0.632 0.012 0.156 0.196 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.496 0.100798 0.616 0.032 0.348 0.004 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.372 0.534821 0.060 0.004 0.008 0.836 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.877 -0.107572 0.404 0.148 0.128 0.272 0.048
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.680 0.263503 0.596 0.164 0.192 0.036 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.834 -0.118227 0.072 0.316 0.020 0.352 0.240
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.745 0.426757 0.272 0.508 0.092 0.124 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.867 0.240729 0.296 0.300 0.268 0.120 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.664 0.459762 0.580 0.048 0.128 0.244 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.372 0.534821 0.060 0.004 0.008 0.836 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.559 0.487405 0.656 0.004 0.188 0.152 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.408 0.558648 0.812 0.016 0.084 0.088 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.482 0.584305 0.284 0.012 0.676 0.000 0.028
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.614 0.447259 0.656 0.072 0.084 0.188 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 4 0.767 0.109239 0.352 0.232 0.044 0.368 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.450 0.560432 0.356 0.004 0.004 0.632 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.717 0.332299 0.224 0.504 0.020 0.240 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.493 0.512827 0.372 0.012 0.600 0.000 0.016
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.295 0.558657 0.884 0.016 0.044 0.056 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.652 0.324749 0.632 0.152 0.168 0.036 0.012
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.560 -0.185299 0.500 0.016 0.444 0.000 0.040
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.782 0.194435 0.232 0.408 0.052 0.300 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.296 0.551132 0.880 0.012 0.068 0.040 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.489 0.520775 0.756 0.032 0.140 0.072 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.417 0.524586 0.796 0.012 0.132 0.060 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.404 0.428284 0.784 0.008 0.024 0.180 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.218 0.599498 0.080 0.000 0.008 0.908 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.425 0.340966 0.736 0.008 0.020 0.236 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.720 0.286278 0.156 0.268 0.528 0.020 0.028
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.651 0.446925 0.132 0.040 0.612 0.004 0.212
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.769 0.344325 0.112 0.484 0.300 0.088 0.016
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.362 0.552801 0.848 0.016 0.048 0.084 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.656 0.506858 0.652 0.112 0.128 0.100 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.549 0.471266 0.684 0.016 0.192 0.108 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.509 0.136286 0.648 0.012 0.028 0.308 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.703 0.525825 0.000 0.176 0.040 0.396 0.364 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.160 0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.466 0.616343 0.156 0.068 0.740 0.008 0.028 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.854 -0.144997 0.320 0.224 0.132 0.012 0.056 0.256
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.757 0.366758 0.160 0.372 0.000 0.004 0.264 0.200
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.505 0.305870 0.432 0.024 0.516 0.024 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.764 0.574417 0.272 0.440 0.128 0.000 0.048 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.310 0.591563 0.864 0.024 0.076 0.000 0.016 0.020
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.463 0.267362 0.484 0.012 0.488 0.004 0.012 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.750 0.169699 0.084 0.136 0.492 0.052 0.232 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.405 0.526604 0.048 0.112 0.020 0.000 0.800 0.020
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.350 0.574564 0.824 0.020 0.124 0.000 0.020 0.012
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.703 0.048487 0.128 0.316 0.016 0.000 0.456 0.084
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.563 0.558029 0.708 0.068 0.104 0.004 0.076 0.040
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.637 0.069220 0.336 0.252 0.000 0.004 0.008 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.499 0.419776 0.668 0.044 0.256 0.004 0.020 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.160 0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.684 0.396495 0.060 0.244 0.052 0.008 0.560 0.076
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.748 0.366769 0.156 0.364 0.000 0.000 0.268 0.212
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.409 0.589162 0.016 0.092 0.116 0.000 0.776 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.271 0.684786 0.000 0.028 0.084 0.876 0.008 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.777 0.443617 0.152 0.460 0.080 0.000 0.220 0.088
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.767 0.418536 0.264 0.200 0.032 0.000 0.096 0.408
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.665 0.475334 0.032 0.116 0.176 0.088 0.588 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.393 0.588382 0.216 0.040 0.004 0.000 0.000 0.740
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.587 0.510064 0.024 0.100 0.240 0.024 0.612 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.585 -0.158223 0.456 0.048 0.452 0.016 0.012 0.016
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#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.482 -0.052320 0.548 0.008 0.404 0.000 0.040 0.000
#> 1122039D-5785-4F70-9916-17C585453512 6 0.324 0.492582 0.024 0.024 0.000 0.104 0.004 0.844
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.849 -0.076880 0.356 0.220 0.096 0.004 0.112 0.212
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.684 0.312227 0.536 0.104 0.168 0.004 0.184 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 6 0.827 -0.244047 0.028 0.196 0.004 0.256 0.216 0.300
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.751 0.092226 0.228 0.176 0.048 0.000 0.468 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.730 0.532161 0.216 0.480 0.204 0.000 0.048 0.052
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.650 0.511349 0.588 0.068 0.124 0.004 0.016 0.200
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 6 0.324 0.492582 0.024 0.024 0.000 0.104 0.004 0.844
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.574 0.487451 0.632 0.024 0.204 0.004 0.008 0.128
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.441 0.591319 0.792 0.024 0.092 0.008 0.024 0.060
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.414 0.618721 0.180 0.036 0.760 0.016 0.008 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.639 0.470456 0.616 0.156 0.080 0.008 0.012 0.128
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.756 0.491708 0.260 0.396 0.028 0.004 0.060 0.252
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.471 0.509929 0.352 0.048 0.004 0.000 0.000 0.596
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.750 -0.235501 0.144 0.332 0.000 0.008 0.356 0.160
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.449 0.565884 0.300 0.020 0.660 0.008 0.012 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.396 0.597737 0.820 0.060 0.068 0.004 0.012 0.036
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.660 0.372246 0.576 0.092 0.144 0.004 0.176 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.548 0.213305 0.432 0.044 0.488 0.032 0.004 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.761 0.377865 0.140 0.396 0.012 0.000 0.256 0.196
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.359 0.587338 0.840 0.028 0.084 0.004 0.016 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.529 0.535160 0.712 0.028 0.160 0.004 0.044 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.443 0.542153 0.776 0.024 0.136 0.008 0.020 0.036
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.445 0.519170 0.756 0.076 0.016 0.004 0.004 0.144
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.160 0.557185 0.028 0.024 0.000 0.008 0.000 0.940
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.476 0.465343 0.724 0.080 0.012 0.008 0.004 0.172
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.744 0.137922 0.080 0.220 0.488 0.024 0.176 0.012
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.550 0.394962 0.060 0.032 0.668 0.208 0.032 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.733 0.467605 0.076 0.144 0.176 0.004 0.536 0.064
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.432 0.597784 0.796 0.080 0.056 0.004 0.012 0.052
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.674 0.523474 0.612 0.116 0.128 0.004 0.076 0.064
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.532 0.469237 0.664 0.028 0.212 0.000 0.008 0.088
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.561 0.279663 0.620 0.104 0.016 0.004 0.008 0.248
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.641 0.845 0.4932 0.499 0.499
#> 3 3 0.622 0.812 0.885 0.3320 0.661 0.424
#> 4 4 0.593 0.693 0.818 0.0938 0.818 0.550
#> 5 5 0.642 0.641 0.777 0.0677 0.901 0.686
#> 6 6 0.682 0.624 0.745 0.0531 0.894 0.601
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.7476 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.8661 0.5659 0.712 0.288
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.8861 0.6115 0.304 0.696
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.8813 0.5500 0.700 0.300
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.9998 -0.1483 0.492 0.508
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.9732 0.5119 0.404 0.596
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5294 0.6621 0.120 0.880
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.8303 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.9522 0.5508 0.372 0.628
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.9710 0.5175 0.400 0.600
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.7476 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5519 0.7012 0.872 0.128
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3879 0.6917 0.076 0.924
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.8909 0.3449 0.692 0.308
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.8499 0.5802 0.724 0.276
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.9775 0.4991 0.412 0.588
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.8661 0.5659 0.712 0.288
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.7476 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.9710 0.1264 0.400 0.600
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.7476 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0672 0.7456 0.008 0.992
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.7476 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8303 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.7476 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.8303 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.7476 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.9754 0.5061 0.408 0.592
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.8303 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.1633 0.8118 0.976 0.024
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.8303 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.7219 0.5891 0.800 0.200
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.7476 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.9170 0.5022 0.668 0.332
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.8303 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.9775 0.4991 0.412 0.588
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.8661 0.5659 0.712 0.288
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.8327 0.5946 0.736 0.264
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.8303 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.8303 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.9129 0.5092 0.672 0.328
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0376 0.8275 0.996 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.8303 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.7476 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8303 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.8555 0.5755 0.720 0.280
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.9732 0.5119 0.404 0.596
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.7476 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.8303 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 0.9954 0.3981 0.460 0.540
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.3431 0.7024 0.064 0.936
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.8303 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.6247 0.6639 0.844 0.156
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.7476 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.9754 0.5058 0.408 0.592
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.8303 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2043 0.8096 0.968 0.032
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.7476 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.9754 0.3714 0.592 0.408
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.9710 0.5175 0.400 0.600
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.8861 0.3606 0.304 0.696
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.8303 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.5519 0.6387 0.128 0.872
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.8303 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.8303 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.8207 0.4772 0.744 0.256
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.9732 0.5119 0.404 0.596
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.7476 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.8303 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.8303 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.8303 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.7476 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.5408 0.7094 0.124 0.876
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.7476 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.7476 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.8861 0.6115 0.304 0.696
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.8661 0.5659 0.712 0.288
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.9732 0.5119 0.404 0.596
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0000 0.7476 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.9491 0.1513 0.632 0.368
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.8861 0.6115 0.304 0.696
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.8303 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.7476 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.8303 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.8713 0.6194 0.292 0.708
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.8303 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.7476 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.8303 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.9393 0.5674 0.356 0.644
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.8303 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.7476 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.8303 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.9954 0.3977 0.460 0.540
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0000 0.8303 1.000 0.000
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#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.9754 0.1034 0.408 0.592
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0376 0.7455 0.004 0.996
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.8303 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.8713 0.5614 0.708 0.292
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.8303 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.8303 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.9427 0.5635 0.360 0.640
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0376 0.8276 0.996 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.6887 0.5691 0.184 0.816
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.8303 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.9988 -0.1147 0.480 0.520
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.9710 0.0644 0.600 0.400
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3274 0.7788 0.940 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.9795 0.4920 0.416 0.584
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.9732 0.5119 0.404 0.596
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.8909 0.3517 0.308 0.692
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.8303 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.8303 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.8303 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.8303 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.8763 0.5550 0.704 0.296
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.8303 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.7476 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.7950 0.6538 0.240 0.760
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.7476 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.8303 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0938 0.8231 0.988 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.8303 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.8303 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4397 0.865972 0.028 0.856 0.116
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3826 0.809596 0.868 0.124 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1964 0.870029 0.000 0.056 0.944
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.4068 0.818158 0.864 0.120 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4883 0.730644 0.208 0.788 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1753 0.875971 0.000 0.048 0.952
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5677 0.755928 0.160 0.792 0.048
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.5254 0.695660 0.264 0.000 0.736
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.1950 0.878661 0.008 0.040 0.952
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1585 0.857627 0.028 0.008 0.964
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2773 0.894697 0.024 0.928 0.048
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.3500 0.841996 0.116 0.004 0.880
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0661 0.911387 0.008 0.988 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.8255 0.586005 0.252 0.128 0.620
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.1905 0.872783 0.956 0.028 0.016
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.1832 0.878774 0.008 0.036 0.956
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.4139 0.814486 0.860 0.124 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0661 0.911387 0.008 0.988 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2434 0.894083 0.024 0.940 0.036
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0592 0.913334 0.000 0.988 0.012
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.6087 0.777705 0.076 0.780 0.144
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0237 0.912217 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0592 0.872899 0.988 0.000 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0424 0.913367 0.000 0.992 0.008
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1289 0.879311 0.968 0.000 0.032
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0892 0.911810 0.000 0.980 0.020
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.1529 0.878154 0.000 0.040 0.960
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4842 0.718258 0.776 0.000 0.224
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5285 0.714270 0.244 0.004 0.752
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.4047 0.820768 0.148 0.004 0.848
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2955 0.861804 0.080 0.008 0.912
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0592 0.913334 0.000 0.988 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.3965 0.805670 0.860 0.132 0.008
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.3816 0.821049 0.148 0.000 0.852
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.1289 0.878701 0.000 0.032 0.968
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.3120 0.847239 0.908 0.080 0.012
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5178 0.655671 0.744 0.256 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.5431 0.666027 0.284 0.000 0.716
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1411 0.879136 0.964 0.000 0.036
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.4139 0.814486 0.860 0.124 0.016
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.5138 0.712697 0.252 0.000 0.748
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.5754 0.644072 0.296 0.004 0.700
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0424 0.913367 0.000 0.992 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.1643 0.861731 0.956 0.000 0.044
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.3610 0.838027 0.888 0.096 0.016
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1529 0.877154 0.000 0.040 0.960
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.5070 0.737425 0.004 0.772 0.224
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5560 0.579074 0.700 0.000 0.300
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.2280 0.860370 0.052 0.008 0.940
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1832 0.899057 0.008 0.956 0.036
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.6286 0.067469 0.536 0.000 0.464
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.2301 0.866703 0.060 0.004 0.936
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0424 0.912743 0.008 0.992 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.1643 0.877394 0.000 0.044 0.956
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1411 0.879136 0.964 0.000 0.036
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1015 0.870495 0.980 0.008 0.012
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0424 0.913367 0.000 0.992 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6432 0.256885 0.428 0.568 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.1643 0.875881 0.000 0.044 0.956
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0592 0.910578 0.012 0.988 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.5722 0.650585 0.292 0.004 0.704
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0747 0.909384 0.016 0.984 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3192 0.845665 0.888 0.000 0.112
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.5733 0.542193 0.676 0.000 0.324
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.1647 0.866045 0.036 0.004 0.960
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1289 0.878185 0.000 0.032 0.968
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.2903 0.893085 0.028 0.924 0.048
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.1860 0.861438 0.948 0.000 0.052
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.4293 0.811455 0.164 0.004 0.832
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1411 0.879136 0.964 0.000 0.036
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0237 0.912217 0.004 0.996 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.5970 0.812904 0.060 0.780 0.160
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.912957 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.1411 0.906437 0.000 0.964 0.036
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.2066 0.870113 0.000 0.060 0.940
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.4068 0.818158 0.864 0.120 0.016
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2063 0.878577 0.008 0.044 0.948
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.1860 0.903331 0.000 0.948 0.052
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1950 0.878612 0.008 0.040 0.952
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.2066 0.870113 0.000 0.060 0.940
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5420 0.682499 0.752 0.008 0.240
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0592 0.913334 0.000 0.988 0.012
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.3267 0.844880 0.884 0.000 0.116
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.1964 0.870029 0.000 0.056 0.944
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1289 0.879311 0.968 0.000 0.032
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0424 0.913367 0.000 0.992 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1289 0.879311 0.968 0.000 0.032
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1643 0.875881 0.000 0.044 0.956
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.4504 0.756024 0.804 0.000 0.196
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0424 0.913367 0.000 0.992 0.008
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.6225 0.339453 0.432 0.000 0.568
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.1950 0.878612 0.008 0.040 0.952
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.3412 0.839857 0.876 0.000 0.124
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0237 0.912998 0.000 0.996 0.004
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.5706 0.605558 0.320 0.000 0.680
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.2903 0.893085 0.028 0.924 0.048
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1031 0.906917 0.024 0.976 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.1643 0.904473 0.000 0.956 0.044
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.4068 0.818158 0.864 0.120 0.016
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.912957 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.3619 0.826701 0.864 0.000 0.136
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1860 0.875876 0.948 0.000 0.052
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.4842 0.731254 0.000 0.776 0.224
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.1964 0.896482 0.000 0.944 0.056
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.3412 0.838317 0.876 0.000 0.124
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.3272 0.809010 0.104 0.004 0.892
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.4209 0.822398 0.856 0.016 0.128
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.1950 0.872280 0.040 0.008 0.952
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0592 0.913334 0.000 0.988 0.012
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.1643 0.861731 0.956 0.000 0.044
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6225 0.277812 0.432 0.568 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.5138 0.666764 0.252 0.748 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0424 0.913367 0.000 0.992 0.008
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.2280 0.860370 0.052 0.008 0.940
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.6451 0.577121 0.292 0.684 0.024
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0424 0.913452 0.000 0.992 0.008
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.1585 0.857627 0.028 0.008 0.964
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.912957 0.000 1.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.1832 0.878768 0.008 0.036 0.956
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.2165 0.857919 0.936 0.000 0.064
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.5497 0.652541 0.292 0.000 0.708
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1411 0.879136 0.964 0.000 0.036
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.1529 0.895097 0.040 0.960 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.1711 0.857959 0.032 0.008 0.960
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.4874 0.844036 0.028 0.828 0.144
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.1636 0.876069 0.964 0.016 0.020
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.4931 0.720285 0.784 0.212 0.004
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.2339 0.872342 0.048 0.012 0.940
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.1529 0.878580 0.960 0.000 0.040
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.5919 0.625435 0.276 0.712 0.012
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.3340 0.840339 0.120 0.000 0.880
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.1525 0.904004 0.004 0.964 0.032
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.2810 0.875778 0.036 0.036 0.928
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.2176 0.875820 0.032 0.020 0.948
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.2165 0.872907 0.936 0.000 0.064
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.1643 0.875881 0.000 0.044 0.956
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.4068 0.818158 0.864 0.120 0.016
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.912957 0.000 1.000 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.1411 0.879136 0.964 0.000 0.036
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0592 0.913334 0.000 0.988 0.012
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.1529 0.877154 0.000 0.040 0.960
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#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1753 0.875971 0.000 0.048 0.952
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0747 0.909628 0.016 0.984 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.6274 0.252916 0.456 0.000 0.544
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.4346 0.780779 0.184 0.000 0.816
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.6309 -0.087494 0.504 0.000 0.496
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3482 0.837289 0.872 0.000 0.128
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.4059 0.810240 0.860 0.128 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4178 0.788789 0.828 0.000 0.172
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.3879 0.822480 0.000 0.848 0.152
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2496 0.862403 0.004 0.068 0.928
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0424 0.913452 0.000 0.992 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.5497 0.652356 0.292 0.000 0.708
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6081 0.461100 0.652 0.004 0.344
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5497 0.652541 0.292 0.000 0.708
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1964 0.875610 0.944 0.000 0.056
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5249 0.7060 0.044 0.708 0.000 0.248
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0376 0.8770 0.000 0.004 0.992 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4746 0.5881 0.008 0.688 0.000 0.304
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0336 0.8804 0.008 0.000 0.992 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4656 0.7065 0.000 0.784 0.056 0.160
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3400 0.7449 0.820 0.000 0.180 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0469 0.8797 0.012 0.000 0.988 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3301 0.7968 0.048 0.000 0.876 0.076
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.4466 0.7603 0.036 0.784 0.000 0.180
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4761 0.5340 0.628 0.000 0.372 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.4103 0.7418 0.000 0.744 0.000 0.256
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7158 0.5903 0.632 0.176 0.164 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.5288 0.4760 0.472 0.008 0.000 0.520
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.2814 0.7867 0.132 0.000 0.868 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4222 0.7291 0.000 0.728 0.000 0.272
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5126 0.5083 0.004 0.552 0.000 0.444
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.8167 -0.1277 0.016 0.380 0.216 0.388
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2589 0.8047 0.000 0.884 0.000 0.116
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.1867 0.6889 0.928 0.000 0.000 0.072
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2281 0.8044 0.000 0.904 0.000 0.096
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3486 0.5502 0.812 0.000 0.000 0.188
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.2976 0.8000 0.000 0.872 0.008 0.120
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0895 0.8771 0.020 0.000 0.976 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2530 0.7613 0.896 0.000 0.100 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4679 0.5674 0.648 0.000 0.352 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4164 0.6850 0.736 0.000 0.264 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2589 0.8027 0.116 0.000 0.884 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.3837 0.7235 0.776 0.000 0.224 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.1940 0.8410 0.076 0.000 0.924 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.5607 0.4284 0.484 0.020 0.000 0.496
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5755 0.3703 0.624 0.332 0.000 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.5143 0.3264 0.540 0.000 0.456 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3801 0.4975 0.780 0.000 0.000 0.220
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3569 0.7383 0.804 0.000 0.196 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3569 0.7385 0.804 0.000 0.196 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0524 0.8092 0.000 0.988 0.004 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3569 0.6310 0.804 0.000 0.000 0.196
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.5688 -0.3470 0.512 0.024 0.000 0.464
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0188 0.8806 0.004 0.000 0.996 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.7028 0.0177 0.000 0.380 0.496 0.124
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.2859 0.7616 0.880 0.000 0.112 0.008
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.6791 0.1598 0.392 0.000 0.508 0.100
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2589 0.8018 0.000 0.884 0.000 0.116
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2831 0.7607 0.876 0.000 0.120 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4103 0.5895 0.256 0.000 0.744 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.4730 0.5717 0.000 0.636 0.000 0.364
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.1637 0.8528 0.060 0.000 0.940 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1557 0.7100 0.944 0.000 0.000 0.056
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1792 0.6974 0.932 0.000 0.000 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0336 0.8095 0.000 0.992 0.000 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.5231 0.5434 0.028 0.676 0.000 0.296
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0592 0.8787 0.016 0.000 0.984 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.4746 0.6268 0.000 0.632 0.000 0.368
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3400 0.7449 0.820 0.000 0.180 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.3494 0.7221 0.000 0.824 0.004 0.172
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.2245 0.7418 0.932 0.008 0.040 0.020
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.2647 0.7611 0.880 0.000 0.120 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.5966 0.5068 0.280 0.000 0.648 0.072
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0188 0.8806 0.004 0.000 0.996 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5052 0.7157 0.036 0.720 0.000 0.244
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2799 0.7006 0.884 0.008 0.000 0.108
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3837 0.7260 0.776 0.000 0.224 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1637 0.7069 0.940 0.000 0.000 0.060
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.4222 0.7013 0.000 0.728 0.000 0.272
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7761 0.3992 0.232 0.580 0.048 0.140
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1004 0.8075 0.000 0.972 0.004 0.024
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.6308 0.5914 0.000 0.648 0.232 0.120
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.0376 0.8770 0.000 0.004 0.992 0.004
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0188 0.8787 0.000 0.000 0.996 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.1854 0.8123 0.000 0.940 0.012 0.048
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.8800 0.000 0.000 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.0376 0.8770 0.000 0.004 0.992 0.004
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.4144 0.7254 0.828 0.104 0.068 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.2976 0.8000 0.000 0.872 0.008 0.120
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.2007 0.7470 0.940 0.020 0.036 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0564 0.8782 0.004 0.004 0.988 0.004
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.3266 0.5818 0.832 0.000 0.000 0.168
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0895 0.8083 0.000 0.976 0.004 0.020
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.2647 0.6475 0.880 0.000 0.000 0.120
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.8800 0.000 0.000 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.2542 0.7591 0.904 0.000 0.084 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1004 0.8075 0.000 0.972 0.004 0.024
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.3306 0.7531 0.840 0.000 0.156 0.004
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.2408 0.8153 0.104 0.000 0.896 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.2944 0.7457 0.900 0.052 0.044 0.004
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.3356 0.7465 0.824 0.000 0.176 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.5137 0.7123 0.040 0.716 0.000 0.244
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.4331 0.6074 0.000 0.712 0.000 0.288
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.2704 0.8002 0.000 0.876 0.000 0.124
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0707 0.8082 0.000 0.980 0.000 0.020
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.2179 0.7548 0.924 0.000 0.064 0.012
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1938 0.7505 0.936 0.000 0.052 0.012
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.3442 0.7676 0.068 0.880 0.040 0.012
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.2973 0.8048 0.000 0.884 0.020 0.096
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.2021 0.7520 0.932 0.000 0.056 0.012
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.4696 0.7114 0.056 0.004 0.792 0.148
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.5179 0.8242 0.220 0.000 0.052 0.728
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.2868 0.7812 0.136 0.000 0.864 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1302 0.8108 0.000 0.956 0.000 0.044
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.3688 0.6162 0.792 0.000 0.000 0.208
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.5860 0.2843 0.380 0.580 0.000 0.040
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.4995 0.6132 0.032 0.720 0.000 0.248
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1004 0.8075 0.000 0.972 0.004 0.024
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.6696 0.2378 0.484 0.000 0.428 0.088
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.5860 0.3911 0.040 0.580 0.000 0.380
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.4525 0.7738 0.116 0.000 0.804 0.080
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0895 0.8078 0.000 0.976 0.004 0.020
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0336 0.8804 0.008 0.000 0.992 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.2999 0.6905 0.864 0.000 0.004 0.132
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.5088 0.0853 0.424 0.000 0.572 0.004
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1940 0.6946 0.924 0.000 0.000 0.076
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.1004 0.8070 0.004 0.972 0.000 0.024
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.6730 0.5519 0.212 0.004 0.628 0.156
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.4849 0.7462 0.036 0.760 0.004 0.200
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.4295 0.8603 0.240 0.008 0.000 0.752
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.5169 0.4950 0.696 0.272 0.000 0.032
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.4992 -0.1310 0.476 0.000 0.524 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.1890 0.7173 0.936 0.000 0.008 0.056
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 4 0.4581 0.7745 0.124 0.032 0.028 0.816
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.4898 0.4474 0.584 0.000 0.416 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.2814 0.7809 0.132 0.000 0.868 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.3528 0.7054 0.192 0.000 0.808 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1489 0.7493 0.952 0.000 0.044 0.004
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0376 0.8773 0.000 0.004 0.992 0.004
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0927 0.8087 0.000 0.976 0.008 0.016
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.1637 0.7069 0.940 0.000 0.000 0.060
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0188 0.8806 0.004 0.000 0.996 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.3801 0.6593 0.220 0.000 0.780 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.1004 0.8075 0.000 0.972 0.004 0.024
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0657 0.8090 0.000 0.984 0.004 0.012
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.3047 0.7610 0.872 0.000 0.116 0.012
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#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.2450 0.7565 0.912 0.000 0.072 0.016
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.4284 0.8575 0.224 0.012 0.000 0.764
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.2089 0.7273 0.932 0.000 0.020 0.048
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2647 0.7603 0.880 0.000 0.120 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0376 0.8770 0.000 0.004 0.992 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5397 0.7039 0.772 0.112 0.096 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3668 0.7079 0.000 0.808 0.004 0.188
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2589 0.6517 0.884 0.000 0.000 0.116
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4889 0.6237 0.004 0.636 0.000 0.360
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0336 0.8804 0.008 0.000 0.992 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4382 0.6545 0.704 0.000 0.296 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.6519 0.4757 0.584 0.000 0.320 0.096
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0524 0.8807 0.008 0.000 0.988 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4250 0.6231 0.000 0.724 0.000 0.276
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3105 0.7572 0.856 0.000 0.140 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5284 0.6723 0.696 0.000 0.264 0.040
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.2647 0.7603 0.880 0.000 0.120 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1474 0.7535 0.948 0.000 0.052 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4387 0.8639 0.236 0.012 0.000 0.752
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1867 0.7587 0.928 0.000 0.072 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.6452 0.1621 0.000 0.472 0.460 0.068
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0779 0.8699 0.000 0.004 0.980 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2647 0.8008 0.000 0.880 0.000 0.120
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3539 0.7460 0.820 0.000 0.176 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4537 0.7334 0.824 0.088 0.072 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5360 0.3753 0.552 0.000 0.436 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1489 0.7490 0.952 0.000 0.044 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.4929 0.50910 0.016 0.260 0.000 0.036 0.688
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.1399 0.89483 0.028 0.020 0.000 0.952 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0451 0.83801 0.000 0.008 0.988 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1949 0.89068 0.040 0.012 0.000 0.932 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3319 0.63788 0.000 0.820 0.000 0.160 0.020
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2017 0.83145 0.000 0.008 0.912 0.000 0.080
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.3161 0.66439 0.024 0.872 0.084 0.008 0.012
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4375 0.74835 0.728 0.000 0.032 0.004 0.236
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.1493 0.83284 0.024 0.000 0.948 0.000 0.028
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3292 0.76150 0.016 0.000 0.836 0.008 0.140
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.4375 0.60552 0.000 0.420 0.000 0.004 0.576
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5716 0.66620 0.628 0.000 0.128 0.004 0.240
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.4977 0.59204 0.000 0.472 0.000 0.028 0.500
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5738 0.66358 0.596 0.044 0.024 0.004 0.332
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6507 -0.02373 0.432 0.192 0.000 0.376 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5134 0.69075 0.088 0.000 0.688 0.004 0.220
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.1399 0.89483 0.028 0.020 0.000 0.952 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.5447 0.56037 0.000 0.440 0.000 0.060 0.500
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.6475 0.05535 0.000 0.484 0.000 0.304 0.212
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6939 0.46951 0.000 0.120 0.080 0.568 0.232
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.4101 -0.13332 0.000 0.664 0.000 0.004 0.332
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2569 0.76199 0.892 0.000 0.000 0.068 0.040
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.4659 0.60714 0.000 0.492 0.000 0.012 0.496
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1965 0.75770 0.904 0.000 0.000 0.096 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3257 0.80794 0.052 0.008 0.860 0.000 0.080
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3328 0.79100 0.848 0.004 0.016 0.012 0.120
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4830 0.72202 0.736 0.004 0.120 0.000 0.140
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4316 0.75220 0.748 0.000 0.040 0.004 0.208
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.3911 0.77402 0.084 0.000 0.812 0.004 0.100
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.1904 0.89406 0.028 0.020 0.000 0.936 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4607 0.74771 0.720 0.000 0.048 0.004 0.228
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4365 0.73301 0.036 0.000 0.736 0.004 0.224
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.6630 -0.08013 0.404 0.376 0.000 0.220 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4920 0.30969 0.408 0.568 0.000 0.016 0.008
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.5620 0.45528 0.580 0.000 0.344 0.008 0.068
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.2966 0.68298 0.816 0.000 0.000 0.184 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.2002 0.89297 0.028 0.020 0.000 0.932 0.020
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4552 0.74460 0.716 0.000 0.040 0.004 0.240
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2928 0.79357 0.872 0.004 0.032 0.000 0.092
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0703 0.68710 0.000 0.976 0.000 0.000 0.024
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.4708 0.62250 0.712 0.000 0.000 0.068 0.220
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.6469 0.16062 0.380 0.436 0.000 0.184 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0162 0.83971 0.000 0.000 0.996 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6699 0.37975 0.000 0.080 0.576 0.084 0.260
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.2067 0.79648 0.928 0.000 0.028 0.012 0.032
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.7636 -0.30377 0.312 0.012 0.248 0.028 0.400
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.4452 0.61002 0.000 0.496 0.000 0.004 0.500
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.3573 0.78584 0.832 0.000 0.032 0.012 0.124
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.6406 0.11019 0.380 0.008 0.476 0.000 0.136
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.6073 0.35697 0.000 0.172 0.000 0.564 0.264
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.4443 0.75027 0.044 0.008 0.748 0.000 0.200
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1597 0.77890 0.940 0.000 0.000 0.048 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1430 0.77671 0.944 0.004 0.000 0.052 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0404 0.69579 0.000 0.988 0.000 0.000 0.012
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3608 0.64091 0.040 0.812 0.000 0.148 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.3583 0.76990 0.012 0.000 0.792 0.004 0.192
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.5840 0.51703 0.000 0.416 0.000 0.096 0.488
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3569 0.77483 0.816 0.004 0.028 0.000 0.152
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1877 0.69382 0.000 0.924 0.000 0.064 0.012
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1439 0.78451 0.956 0.016 0.004 0.020 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.3606 0.77288 0.808 0.004 0.024 0.000 0.164
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.6165 0.56771 0.180 0.004 0.640 0.024 0.152
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0290 0.84000 0.000 0.000 0.992 0.000 0.008
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.4928 0.51580 0.012 0.264 0.000 0.040 0.684
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.4302 0.69310 0.720 0.000 0.000 0.032 0.248
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.2515 0.79678 0.904 0.000 0.044 0.008 0.044
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1981 0.77941 0.924 0.000 0.000 0.048 0.028
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.6536 0.09424 0.000 0.220 0.000 0.468 0.312
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7086 0.28300 0.132 0.556 0.020 0.036 0.256
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0451 0.70040 0.000 0.988 0.000 0.004 0.008
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.7107 0.36751 0.000 0.212 0.292 0.028 0.468
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.2361 0.82353 0.000 0.012 0.892 0.000 0.096
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.1701 0.89499 0.028 0.012 0.000 0.944 0.016
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0451 0.83801 0.000 0.008 0.988 0.000 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.4487 -0.00301 0.008 0.660 0.004 0.004 0.324
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0613 0.83787 0.004 0.008 0.984 0.000 0.004
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.0579 0.83792 0.000 0.008 0.984 0.000 0.008
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5086 0.22487 0.576 0.392 0.004 0.004 0.024
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1725 0.79110 0.944 0.024 0.004 0.004 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0486 0.83965 0.004 0.004 0.988 0.000 0.004
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1792 0.76351 0.916 0.000 0.000 0.084 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0451 0.70275 0.000 0.988 0.000 0.004 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1608 0.76966 0.928 0.000 0.000 0.072 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0162 0.83971 0.000 0.000 0.996 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.2312 0.79441 0.912 0.000 0.016 0.012 0.060
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0727 0.70544 0.012 0.980 0.000 0.004 0.004
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.3675 0.78603 0.828 0.000 0.032 0.016 0.124
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.5206 0.71132 0.104 0.008 0.700 0.000 0.188
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.1780 0.79253 0.940 0.028 0.008 0.000 0.024
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.4238 0.75332 0.740 0.000 0.028 0.004 0.228
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.3910 0.54537 0.000 0.272 0.000 0.008 0.720
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3284 0.64231 0.000 0.828 0.000 0.148 0.024
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.4449 0.62047 0.000 0.484 0.000 0.004 0.512
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.1701 0.89499 0.028 0.012 0.000 0.944 0.016
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0510 0.69374 0.000 0.984 0.000 0.000 0.016
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.3257 0.79055 0.856 0.000 0.024 0.016 0.104
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1701 0.79150 0.944 0.000 0.016 0.012 0.028
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.2656 0.67039 0.028 0.896 0.012 0.000 0.064
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.4684 -0.53563 0.000 0.536 0.008 0.004 0.452
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.1815 0.79150 0.940 0.000 0.024 0.016 0.020
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5065 0.61743 0.020 0.004 0.704 0.040 0.232
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.4785 0.75789 0.108 0.008 0.104 0.768 0.012
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.5762 0.61086 0.152 0.000 0.632 0.004 0.212
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.4030 -0.22653 0.000 0.648 0.000 0.000 0.352
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.4822 0.61131 0.704 0.000 0.000 0.076 0.220
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.5034 0.44907 0.260 0.684 0.000 0.028 0.028
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.3090 0.67380 0.052 0.860 0.000 0.088 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0324 0.70382 0.000 0.992 0.000 0.004 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.7276 0.37121 0.420 0.004 0.192 0.028 0.356
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.3652 0.60699 0.004 0.784 0.000 0.200 0.012
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 5 0.4450 0.62065 0.000 0.488 0.000 0.004 0.508
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.6351 0.47850 0.088 0.000 0.476 0.024 0.412
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0510 0.69374 0.000 0.984 0.000 0.000 0.016
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0566 0.83890 0.004 0.000 0.984 0.000 0.012
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.4812 0.61073 0.652 0.000 0.004 0.032 0.312
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.5573 0.25531 0.388 0.000 0.548 0.008 0.056
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1965 0.77758 0.924 0.000 0.000 0.052 0.024
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0671 0.70499 0.004 0.980 0.000 0.016 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.6523 0.37502 0.084 0.000 0.452 0.036 0.428
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6376 0.61954 0.572 0.000 0.160 0.016 0.252
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.1809 0.77382 0.928 0.000 0.000 0.060 0.012
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0609 0.69055 0.000 0.980 0.000 0.000 0.020
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.4306 0.61533 0.000 0.492 0.000 0.000 0.508
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.1399 0.89483 0.028 0.020 0.000 0.952 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0162 0.83938 0.004 0.000 0.996 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.1267 0.78588 0.960 0.000 0.012 0.024 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.6599 0.38657 0.148 0.000 0.452 0.012 0.388
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0162 0.83938 0.004 0.000 0.996 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.6302 0.62501 0.560 0.000 0.128 0.016 0.296
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.3548 0.77227 0.012 0.000 0.796 0.004 0.188
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0162 0.83938 0.004 0.000 0.996 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.4548 0.64529 0.232 0.000 0.716 0.000 0.052
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.5156 0.71153 0.688 0.000 0.092 0.004 0.216
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.4178 0.75662 0.748 0.000 0.028 0.004 0.220
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2416 0.68142 0.012 0.888 0.000 0.100 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.6250 0.29082 0.088 0.352 0.540 0.008 0.012
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.6910 0.05526 0.312 0.000 0.392 0.004 0.292
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.1372 0.83266 0.000 0.016 0.956 0.004 0.024
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.1708 0.79488 0.944 0.004 0.016 0.004 0.032
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.4264 0.59122 0.000 0.376 0.000 0.004 0.620
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0324 0.70382 0.000 0.992 0.000 0.004 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1341 0.77420 0.944 0.000 0.000 0.056 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.5815 0.64225 0.624 0.000 0.152 0.004 0.220
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0510 0.84148 0.000 0.000 0.984 0.000 0.016
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.1774 0.77637 0.932 0.000 0.000 0.052 0.016
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.4117 0.76556 0.788 0.000 0.116 0.000 0.096
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6270 0.42076 0.020 0.604 0.000 0.168 0.208
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.2574 0.82428 0.112 0.012 0.000 0.876 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.1444 0.88650 0.040 0.012 0.000 0.948 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1740 0.77520 0.932 0.000 0.000 0.056 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.6532 -0.00252 0.012 0.432 0.000 0.136 0.420
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.1845 0.77523 0.928 0.000 0.000 0.056 0.016
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.1124 0.78227 0.960 0.000 0.000 0.036 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3851 0.75983 0.016 0.000 0.768 0.004 0.212
#> 1122039D-5785-4F70-9916-17C585453512 4 0.2002 0.89297 0.028 0.020 0.000 0.932 0.020
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6364 0.50877 0.476 0.000 0.076 0.032 0.416
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.5535 0.63619 0.088 0.000 0.620 0.004 0.288
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3477 0.78781 0.000 0.056 0.000 0.832 0.112
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.5631 0.53699 0.000 0.424 0.000 0.076 0.500
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.2491 0.68029 0.024 0.904 0.064 0.004 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.3003 0.79298 0.872 0.000 0.020 0.016 0.092
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.1710 0.89318 0.024 0.012 0.000 0.944 0.020
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.1597 0.78989 0.948 0.000 0.020 0.024 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.3124 0.78630 0.844 0.000 0.016 0.004 0.136
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0798 0.83848 0.000 0.008 0.976 0.000 0.016
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5414 0.09716 0.512 0.440 0.000 0.008 0.040
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1894 0.69175 0.000 0.920 0.000 0.072 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.1764 0.77241 0.928 0.000 0.000 0.064 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5927 -0.41013 0.000 0.468 0.000 0.104 0.428
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1478 0.83405 0.000 0.000 0.936 0.000 0.064
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.5213 0.70868 0.680 0.000 0.092 0.004 0.224
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.6679 -0.48920 0.412 0.000 0.124 0.024 0.440
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.2563 0.81827 0.000 0.008 0.872 0.000 0.120
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3327 0.64132 0.000 0.828 0.000 0.144 0.028
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3521 0.78335 0.824 0.000 0.024 0.008 0.144
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4844 0.75451 0.740 0.000 0.104 0.008 0.148
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3573 0.78584 0.832 0.000 0.032 0.012 0.124
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1278 0.79371 0.960 0.000 0.016 0.004 0.020
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.1399 0.89483 0.028 0.020 0.000 0.952 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1756 0.79535 0.940 0.000 0.016 0.008 0.036
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6095 0.31165 0.000 0.184 0.588 0.004 0.224
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1059 0.83561 0.000 0.008 0.968 0.004 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.4452 0.61002 0.000 0.496 0.000 0.004 0.500
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4240 0.75495 0.756 0.004 0.028 0.004 0.208
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5999 0.56001 0.608 0.264 0.016 0.000 0.112
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5288 0.58831 0.664 0.000 0.260 0.012 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1256 0.79179 0.964 0.004 0.012 0.008 0.012
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.4243 0.48571 0.272 0.032 0.000 0.008 0.688 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0951 0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0405 0.84420 0.008 0.000 0.988 0.000 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.2551 0.84235 0.028 0.008 0.000 0.896 0.016 0.052
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2490 0.81171 0.044 0.892 0.000 0.052 0.012 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.3921 0.50321 0.308 0.000 0.676 0.004 0.012 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.2333 0.80656 0.024 0.912 0.020 0.000 0.016 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3756 0.50572 0.644 0.000 0.000 0.000 0.004 0.352
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.1983 0.82471 0.060 0.000 0.916 0.000 0.012 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2679 0.79565 0.096 0.000 0.864 0.000 0.040 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.2948 0.85787 0.008 0.188 0.000 0.000 0.804 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4633 0.56842 0.640 0.000 0.040 0.000 0.012 0.308
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.3479 0.85616 0.012 0.212 0.000 0.008 0.768 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5341 0.52426 0.632 0.004 0.008 0.000 0.140 0.216
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.5889 0.24157 0.020 0.236 0.000 0.184 0.000 0.560
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4663 0.58515 0.664 0.000 0.244 0.000 0.000 0.092
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0951 0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.3691 0.85028 0.012 0.204 0.000 0.020 0.764 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.6718 0.32039 0.036 0.348 0.000 0.256 0.360 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.2854 0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6054 0.49751 0.044 0.004 0.108 0.556 0.288 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3684 0.15968 0.000 0.628 0.000 0.000 0.372 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.3649 0.54433 0.180 0.004 0.000 0.016 0.016 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.3481 0.83398 0.032 0.192 0.000 0.000 0.776 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0858 0.66961 0.000 0.004 0.000 0.028 0.000 0.968
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.2854 0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4521 0.55084 0.212 0.000 0.716 0.004 0.016 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB 6 0.4382 0.24031 0.416 0.004 0.004 0.000 0.012 0.564
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 6 0.5365 -0.06426 0.380 0.008 0.032 0.008 0.020 0.552
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4589 0.46045 0.580 0.008 0.000 0.004 0.020 0.388
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4737 0.53289 0.248 0.000 0.672 0.000 0.012 0.068
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.2854 0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0405 0.89405 0.000 0.008 0.000 0.988 0.004 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4343 0.44704 0.592 0.000 0.020 0.000 0.004 0.384
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3742 0.39661 0.648 0.000 0.348 0.004 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.5827 0.43311 0.044 0.528 0.000 0.080 0.000 0.348
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3971 0.71830 0.060 0.772 0.000 0.000 0.012 0.156
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 6 0.6062 0.14270 0.204 0.000 0.268 0.000 0.016 0.512
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2003 0.62903 0.000 0.000 0.000 0.116 0.000 0.884
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0405 0.89405 0.000 0.008 0.000 0.988 0.004 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3864 0.51688 0.648 0.000 0.004 0.000 0.004 0.344
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 6 0.4637 0.28464 0.352 0.008 0.000 0.004 0.028 0.608
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0748 0.82969 0.004 0.976 0.004 0.000 0.016 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.5542 0.41383 0.232 0.004 0.000 0.016 0.132 0.616
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.5677 0.57751 0.052 0.624 0.000 0.060 0.012 0.252
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0405 0.84539 0.008 0.000 0.988 0.000 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.5510 0.50919 0.044 0.008 0.628 0.060 0.260 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.3295 0.60275 0.184 0.004 0.004 0.000 0.012 0.796
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.5404 0.48870 0.712 0.008 0.084 0.008 0.112 0.076
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.2883 0.86476 0.000 0.212 0.000 0.000 0.788 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.4109 0.36973 0.328 0.000 0.008 0.000 0.012 0.652
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.6762 0.43921 0.404 0.008 0.224 0.008 0.016 0.340
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.5242 0.38927 0.040 0.036 0.000 0.564 0.360 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5014 0.37782 0.584 0.004 0.364 0.008 0.016 0.024
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.0692 0.67409 0.020 0.000 0.000 0.000 0.004 0.976
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.3313 0.59805 0.152 0.016 0.000 0.012 0.004 0.816
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0508 0.83144 0.004 0.984 0.000 0.000 0.012 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.2291 0.81902 0.044 0.904 0.000 0.040 0.000 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.4070 0.21638 0.568 0.000 0.424 0.004 0.004 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.3934 0.84249 0.016 0.204 0.000 0.028 0.752 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 6 0.4689 -0.19503 0.460 0.008 0.000 0.004 0.020 0.508
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1718 0.82738 0.044 0.932 0.000 0.016 0.008 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.1194 0.67338 0.032 0.004 0.000 0.000 0.008 0.956
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4689 0.31348 0.508 0.008 0.000 0.004 0.020 0.460
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.5791 0.50651 0.208 0.000 0.616 0.000 0.052 0.124
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0547 0.84635 0.020 0.000 0.980 0.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.4112 0.55476 0.224 0.048 0.000 0.004 0.724 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.5156 0.03131 0.528 0.012 0.000 0.004 0.048 0.408
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 6 0.4015 0.55867 0.188 0.008 0.008 0.004 0.028 0.764
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.1297 0.66933 0.040 0.000 0.000 0.000 0.012 0.948
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5458 0.30159 0.040 0.048 0.000 0.532 0.380 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.6887 0.33432 0.276 0.488 0.004 0.012 0.168 0.052
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0508 0.83211 0.004 0.984 0.000 0.000 0.012 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.6030 0.29575 0.040 0.040 0.352 0.036 0.532 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3269 0.73751 0.168 0.008 0.808 0.004 0.012 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0436 0.89461 0.000 0.004 0.000 0.988 0.004 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0405 0.84539 0.008 0.000 0.988 0.000 0.004 0.000
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#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.2854 0.86692 0.000 0.208 0.000 0.000 0.792 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.2847 0.81083 0.048 0.880 0.000 0.036 0.004 0.032
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 6 0.2170 0.65129 0.100 0.000 0.000 0.000 0.012 0.888
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2491 0.74408 0.164 0.000 0.836 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 6 0.6142 0.12706 0.356 0.000 0.112 0.000 0.044 0.488
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.0622 0.67378 0.012 0.000 0.000 0.008 0.000 0.980
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0363 0.83183 0.000 0.988 0.000 0.000 0.012 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.2996 0.85560 0.000 0.228 0.000 0.000 0.772 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0951 0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0363 0.84626 0.012 0.000 0.988 0.000 0.000 0.000
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#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0363 0.84626 0.012 0.000 0.988 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.4022 0.59385 0.708 0.000 0.040 0.000 0.000 0.252
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.3996 0.00835 0.512 0.000 0.484 0.004 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0363 0.84626 0.012 0.000 0.988 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.6477 0.07240 0.148 0.008 0.484 0.004 0.028 0.328
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4692 0.51799 0.600 0.000 0.016 0.004 0.020 0.360
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3986 0.44502 0.608 0.000 0.000 0.004 0.004 0.384
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1167 0.83383 0.012 0.960 0.000 0.008 0.000 0.020
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.5650 0.28837 0.044 0.372 0.536 0.000 0.012 0.036
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4328 0.61344 0.720 0.000 0.100 0.000 0.000 0.180
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.2145 0.82448 0.056 0.008 0.912 0.004 0.020 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 6 0.3360 0.58979 0.148 0.012 0.000 0.004 0.020 0.816
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.2814 0.84840 0.008 0.172 0.000 0.000 0.820 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0508 0.83144 0.004 0.984 0.000 0.000 0.012 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.0551 0.67218 0.000 0.004 0.000 0.008 0.004 0.984
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.5202 0.57434 0.608 0.000 0.056 0.008 0.016 0.312
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.1610 0.81336 0.084 0.000 0.916 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.0508 0.67412 0.012 0.000 0.000 0.004 0.000 0.984
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 6 0.5208 0.41628 0.260 0.008 0.052 0.004 0.024 0.652
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6168 0.50243 0.244 0.580 0.000 0.044 0.120 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.3508 0.58429 0.000 0.004 0.000 0.704 0.000 0.292
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.1285 0.87663 0.000 0.004 0.000 0.944 0.000 0.052
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.0767 0.67376 0.012 0.000 0.000 0.008 0.004 0.976
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.6503 0.01043 0.236 0.388 0.000 0.024 0.352 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.0622 0.67378 0.012 0.000 0.000 0.008 0.000 0.980
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.0291 0.67472 0.004 0.000 0.000 0.000 0.004 0.992
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4072 0.10832 0.544 0.000 0.448 0.000 0.000 0.008
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0779 0.89095 0.008 0.008 0.000 0.976 0.008 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.5737 0.35616 0.652 0.008 0.028 0.008 0.140 0.164
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4219 0.47490 0.660 0.000 0.304 0.000 0.000 0.036
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3359 0.76641 0.024 0.020 0.000 0.820 0.136 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.4234 0.81880 0.024 0.224 0.000 0.028 0.724 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.2501 0.79822 0.004 0.896 0.056 0.000 0.028 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.3840 0.50568 0.264 0.004 0.004 0.000 0.012 0.716
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0810 0.89188 0.008 0.004 0.000 0.976 0.008 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.1624 0.67201 0.044 0.000 0.008 0.000 0.012 0.936
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.3930 0.12360 0.420 0.000 0.000 0.000 0.004 0.576
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0837 0.84272 0.020 0.000 0.972 0.004 0.004 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4958 0.63405 0.088 0.692 0.000 0.004 0.020 0.196
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1718 0.82738 0.044 0.932 0.000 0.016 0.008 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0914 0.67334 0.016 0.000 0.000 0.016 0.000 0.968
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.4969 0.64066 0.036 0.332 0.000 0.028 0.604 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3052 0.66221 0.216 0.000 0.780 0.000 0.004 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4734 0.54631 0.624 0.000 0.028 0.004 0.016 0.328
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3497 0.55868 0.832 0.000 0.056 0.000 0.032 0.080
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3855 0.57460 0.276 0.000 0.704 0.004 0.016 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.2606 0.80970 0.044 0.888 0.000 0.048 0.020 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 6 0.4083 0.00413 0.460 0.000 0.000 0.000 0.008 0.532
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5145 0.29188 0.500 0.000 0.072 0.000 0.004 0.424
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.4153 0.34489 0.340 0.000 0.008 0.000 0.012 0.640
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.3118 0.61304 0.124 0.012 0.000 0.004 0.020 0.840
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0951 0.89486 0.000 0.008 0.000 0.968 0.004 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 6 0.3676 0.56228 0.184 0.012 0.000 0.004 0.020 0.780
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4865 0.51185 0.024 0.056 0.664 0.000 0.256 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1564 0.82818 0.040 0.000 0.936 0.000 0.024 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.3320 0.85678 0.016 0.212 0.000 0.000 0.772 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4467 0.47915 0.592 0.004 0.000 0.004 0.020 0.380
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.6649 -0.04381 0.284 0.332 0.000 0.000 0.028 0.356
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.4936 0.44869 0.212 0.000 0.104 0.000 0.012 0.672
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.2558 0.64424 0.084 0.012 0.000 0.004 0.016 0.884
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.483 0.590 0.814 0.4981 0.507 0.507
#> 3 3 0.856 0.899 0.957 0.3412 0.701 0.474
#> 4 4 0.709 0.629 0.811 0.1166 0.845 0.582
#> 5 5 0.662 0.568 0.764 0.0630 0.874 0.568
#> 6 6 0.740 0.629 0.815 0.0425 0.886 0.535
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.9988 0.7655 0.480 0.520
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.0000 0.3742 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.4815 0.1700 0.896 0.104
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.3742 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2423 0.4156 0.040 0.960
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.4101 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9866 0.7409 0.432 0.568
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.9988 0.7357 0.520 0.480
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0000 0.4101 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.4101 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.9988 0.7655 0.480 0.520
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.9635 0.7016 0.612 0.388
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.9881 0.7431 0.436 0.564
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7602 0.5735 0.780 0.220
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.0000 0.3742 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.4101 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0000 0.3742 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.9988 0.7655 0.480 0.520
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.9248 0.6853 0.340 0.660
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.9988 0.7655 0.480 0.520
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.9988 0.7655 0.480 0.520
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.9988 0.7655 0.480 0.520
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.9988 0.7357 0.520 0.480
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.9988 0.7655 0.480 0.520
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.9988 0.7357 0.520 0.480
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.9988 0.7655 0.480 0.520
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.4101 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.9988 0.7357 0.520 0.480
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.9988 0.7357 0.520 0.480
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.9988 0.7357 0.520 0.480
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.9970 0.7317 0.532 0.468
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.9988 0.7655 0.480 0.520
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.3742 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.9988 0.7357 0.520 0.480
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.4101 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.0000 0.3742 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.3742 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.9988 0.7357 0.520 0.480
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.9988 0.7357 0.520 0.480
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.0000 0.3742 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.9988 0.7357 0.520 0.480
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.9988 0.7357 0.520 0.480
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.9988 0.7655 0.480 0.520
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.9988 0.7357 0.520 0.480
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0000 0.3742 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.4101 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.9988 0.7655 0.480 0.520
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.9988 0.7357 0.520 0.480
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.7299 0.5827 0.796 0.204
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.9988 0.7655 0.480 0.520
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.9988 0.7357 0.520 0.480
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.9635 0.7016 0.612 0.388
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.9988 0.7655 0.480 0.520
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.4101 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.9988 0.7357 0.520 0.480
#> 311D089C-33F1-4722-9118-F56427C5C128 2 0.7745 -0.2545 0.228 0.772
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.9988 0.7655 0.480 0.520
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.3742 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0000 0.4101 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.9580 0.7110 0.380 0.620
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.9988 0.7357 0.520 0.480
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.9635 0.7156 0.388 0.612
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.9988 0.7357 0.520 0.480
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.9988 0.7357 0.520 0.480
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.9248 0.6695 0.660 0.340
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0000 0.4101 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.9988 0.7655 0.480 0.520
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.9988 0.7357 0.520 0.480
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.9988 0.7357 0.520 0.480
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.9988 0.7357 0.520 0.480
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.9988 0.7655 0.480 0.520
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.9963 0.7571 0.464 0.536
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.9988 0.7655 0.480 0.520
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.9988 0.7655 0.480 0.520
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.0000 0.4101 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.0000 0.3742 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0000 0.4101 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.9988 0.7655 0.480 0.520
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.6048 0.5159 0.852 0.148
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.5519 0.0973 0.872 0.128
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.9988 0.7357 0.520 0.480
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.9988 0.7655 0.480 0.520
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.9988 0.7357 0.520 0.480
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.5629 0.0843 0.868 0.132
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.9988 0.7357 0.520 0.480
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.9988 0.7655 0.480 0.520
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.9988 0.7357 0.520 0.480
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.0000 0.4101 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.9988 0.7357 0.520 0.480
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.9988 0.7655 0.480 0.520
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.9988 0.7357 0.520 0.480
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.2778 0.4530 0.952 0.048
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.9988 0.7357 0.520 0.480
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.9988 0.7655 0.480 0.520
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.9988 0.7357 0.520 0.480
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.9988 0.7655 0.480 0.520
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.9580 0.7110 0.380 0.620
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.9988 0.7655 0.480 0.520
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 2 0.0000 0.3742 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.9988 0.7655 0.480 0.520
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.9988 0.7357 0.520 0.480
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.9988 0.7357 0.520 0.480
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.9993 0.7618 0.484 0.516
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.9988 0.7655 0.480 0.520
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.9988 0.7357 0.520 0.480
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.2948 0.3198 0.948 0.052
#> D09064DF-70AE-4A49-9F70-2A8093C96724 2 0.6801 -0.1168 0.180 0.820
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.9552 0.6963 0.624 0.376
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.9988 0.7655 0.480 0.520
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.9998 0.7255 0.508 0.492
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.0000 0.3742 0.000 1.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.4562 0.4727 0.096 0.904
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.9988 0.7655 0.480 0.520
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.9580 0.6980 0.620 0.380
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.0000 0.3742 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.9988 0.7655 0.480 0.520
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0000 0.4101 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.9988 0.7655 0.480 0.520
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.0000 0.4101 1.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.9988 0.7357 0.520 0.480
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.9988 0.7357 0.520 0.480
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.9988 0.7357 0.520 0.480
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.6801 0.5541 0.180 0.820
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.0672 0.4175 0.992 0.008
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.9988 0.7655 0.480 0.520
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 2 0.3431 0.2380 0.064 0.936
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.0000 0.3742 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.9000 0.6632 0.684 0.316
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.9988 0.7357 0.520 0.480
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.9988 0.7655 0.480 0.520
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.9710 0.7067 0.600 0.400
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.9988 0.7655 0.480 0.520
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.3584 0.4505 0.932 0.068
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.8081 0.6180 0.752 0.248
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.9988 0.7357 0.520 0.480
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 1 0.2778 0.3130 0.952 0.048
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 2 0.0000 0.3742 0.000 1.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.9988 0.7655 0.480 0.520
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.9988 0.7357 0.520 0.480
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.9988 0.7655 0.480 0.520
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 1 0.0000 0.4101 1.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 1 0.0000 0.4101 1.000 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.9988 0.7655 0.480 0.520
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.9988 0.7655 0.480 0.520
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.9988 0.7357 0.520 0.480
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.9988 0.7655 0.480 0.520
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.9988 0.7655 0.480 0.520
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.9988 0.7357 0.520 0.480
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 1 0.0000 0.4101 1.000 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.9988 0.7357 0.520 0.480
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.9988 0.7655 0.480 0.520
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 1 0.0000 0.4101 1.000 0.000
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#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 1 0.0000 0.4101 1.000 0.000
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 1 1.0000 0.7219 0.504 0.496
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 1 0.0376 0.4126 0.996 0.004
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 1 0.0000 0.4101 1.000 0.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.9988 0.7357 0.520 0.480
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 1 0.0376 0.4138 0.996 0.004
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 1 0.4562 0.4680 0.904 0.096
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.9988 0.7655 0.480 0.520
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.9988 0.7357 0.520 0.480
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.9988 0.7655 0.480 0.520
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.9988 0.7655 0.480 0.520
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 1 0.5629 0.0843 0.868 0.132
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.7950 0.6104 0.760 0.240
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.9988 0.7655 0.480 0.520
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.9988 0.7357 0.520 0.480
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 1 0.0000 0.4101 1.000 0.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 1 0.0000 0.4101 1.000 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.8661 0.6443 0.712 0.288
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.9988 0.7357 0.520 0.480
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.9988 0.7655 0.480 0.520
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.9988 0.7655 0.480 0.520
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.9988 0.7357 0.520 0.480
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.9988 0.7655 0.480 0.520
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 1 0.0000 0.4101 1.000 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.9988 0.7357 0.520 0.480
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.9988 0.7655 0.480 0.520
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.9988 0.7357 0.520 0.480
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 1 0.0000 0.4101 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.9988 0.7357 0.520 0.480
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.9988 0.7655 0.480 0.520
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.9988 0.7357 0.520 0.480
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.9608 0.6998 0.616 0.384
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 1 0.8144 -0.3047 0.748 0.252
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.0000 0.3742 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.9988 0.7655 0.480 0.520
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.9988 0.7655 0.480 0.520
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.0000 0.4101 1.000 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.1633 0.3993 0.024 0.976
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.7219 0.5722 0.200 0.800
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.9209 0.6823 0.336 0.664
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.0000 0.3742 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.9988 0.7655 0.480 0.520
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.9988 0.7357 0.520 0.480
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.9988 0.7357 0.520 0.480
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.9988 0.7357 0.520 0.480
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.9988 0.7357 0.520 0.480
#> B57C849C-28B1-4315-885C-330B9C9482B3 1 0.0000 0.4101 1.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.9286 0.6878 0.344 0.656
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.9988 0.7655 0.480 0.520
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.9988 0.7655 0.480 0.520
#> 80936433-AA91-4219-98F1-706C36298060 2 0.9988 0.7655 0.480 0.520
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 2 0.0000 0.3742 0.000 1.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.9427 0.6887 0.640 0.360
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.9988 0.7357 0.520 0.480
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.9988 0.7357 0.520 0.480
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.9988 0.7655 0.480 0.520
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.9988 0.7357 0.520 0.480
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.9988 0.7357 0.520 0.480
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.9988 0.7357 0.520 0.480
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.9988 0.7357 0.520 0.480
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.9988 0.7357 0.520 0.480
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.0000 0.4101 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.0000 0.4101 1.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.0000 0.3742 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.9635 -0.5873 0.388 0.612
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.9988 0.7357 0.520 0.480
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.9988 0.7655 0.480 0.520
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.9988 0.7357 0.520 0.480
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.9988 0.7357 0.520 0.480
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0000 0.4101 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.9988 0.7357 0.520 0.480
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.9988 0.7357 0.520 0.480
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.9044 0.6659 0.680 0.320
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.9988 0.7357 0.520 0.480
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0000 0.3742 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.3733 0.2180 0.072 0.928
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.9988 0.7655 0.480 0.520
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.9988 0.7655 0.480 0.520
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.9988 0.7357 0.520 0.480
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.9988 0.7655 0.480 0.520
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.0000 0.4101 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.0000 0.4101 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.9988 0.7357 0.520 0.480
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.9988 0.7655 0.480 0.520
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.0000 0.3742 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.9988 0.7357 0.520 0.480
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.8955 0.6459 0.688 0.312
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.9988 0.7655 0.480 0.520
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.6887 0.5577 0.184 0.816
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.9988 0.7357 0.520 0.480
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.9608 0.6998 0.616 0.384
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.9988 0.7357 0.520 0.480
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.9988 0.7357 0.520 0.480
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.9988 0.7655 0.480 0.520
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.9988 0.7655 0.480 0.520
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.0000 0.3742 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0000 0.4101 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.9988 0.7357 0.520 0.480
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.4101 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.0000 0.4101 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.9608 0.6998 0.616 0.384
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.0000 0.4101 1.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 1 0.6801 -0.0849 0.820 0.180
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.9988 0.7357 0.520 0.480
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.9988 0.7357 0.520 0.480
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.9988 0.7357 0.520 0.480
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.3742 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.9608 0.7132 0.384 0.616
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5737 0.5284 0.864 0.136
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 1.0000 -0.7435 0.504 0.496
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.9988 0.7357 0.520 0.480
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.9988 0.7655 0.480 0.520
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.9988 0.7655 0.480 0.520
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.9988 0.7357 0.520 0.480
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.9608 0.6998 0.616 0.384
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.4101 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.9988 0.7357 0.520 0.480
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.9988 0.7357 0.520 0.480
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.3742 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 2 0.4161 0.1867 0.084 0.916
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.2948 0.2664 0.052 0.948
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.9988 0.7357 0.520 0.480
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.3742 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.9988 0.7357 0.520 0.480
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.9988 0.7357 0.520 0.480
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.4101 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 2 0.0000 0.3742 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.9988 0.7357 0.520 0.480
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.4101 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9460 0.7024 0.364 0.636
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.8555 0.6405 0.280 0.720
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.9988 0.7655 0.480 0.520
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.9988 0.7357 0.520 0.480
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.0000 0.3742 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.9988 0.7357 0.520 0.480
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.9988 0.7357 0.520 0.480
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0000 0.4101 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.9988 0.7357 0.520 0.480
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.9635 0.7156 0.388 0.612
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.9988 0.7357 0.520 0.480
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.6887 0.5581 0.184 0.816
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.9358 0.6838 0.648 0.352
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.9988 0.7357 0.520 0.480
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.6973 0.5710 0.812 0.188
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0000 0.4101 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.9580 0.7110 0.380 0.620
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.9988 0.7357 0.520 0.480
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.9988 0.7357 0.520 0.480
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.9988 0.7357 0.520 0.480
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.9988 0.7357 0.520 0.480
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0000 0.3742 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.9988 0.7357 0.520 0.480
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.9988 0.7655 0.480 0.520
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 1.0000 0.7499 0.496 0.504
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.9988 0.7655 0.480 0.520
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.9988 0.7357 0.520 0.480
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.8909 -0.4430 0.308 0.692
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.9988 0.7357 0.520 0.480
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.9988 0.7357 0.520 0.480
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9540 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0747 0.9456 0.984 0.016 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.9508 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.0000 0.9573 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9540 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.9508 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0424 0.9482 0.008 0.992 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4796 0.7064 0.780 0.000 0.220
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 0.9508 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.9508 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.9540 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.4346 0.7654 0.184 0.000 0.816
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9540 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.9717 0.0424 0.384 0.396 0.220
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.9573 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0000 0.9508 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0424 0.9516 0.992 0.008 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9540 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.9540 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9540 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.4702 0.7232 0.000 0.788 0.212
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9540 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9573 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9540 0.000 1.000 0.000
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#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0592 0.9451 0.012 0.988 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0000 0.9540 0.000 1.000 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.0000 0.9573 1.000 0.000 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.9540 0.000 1.000 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.9573 1.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.9573 1.000 0.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.4702 0.7118 0.788 0.000 0.212
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.9573 1.000 0.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0000 0.9508 0.000 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.9540 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.9540 0.000 1.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9540 0.000 1.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9540 0.000 1.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.9573 1.000 0.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.6111 0.3225 0.000 0.396 0.604
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9573 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9573 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9540 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0000 0.9508 0.000 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9573 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9573 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.9573 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9573 1.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.9508 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0000 0.9508 0.000 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0747 0.9456 0.984 0.016 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.9573 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9573 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.9540 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.9573 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0747 0.9402 0.016 0.000 0.984
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.9508 0.000 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.9573 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.4702 0.7293 0.212 0.000 0.788
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.8526 0.4116 0.120 0.572 0.308
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9573 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.4346 0.7682 0.184 0.816 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.0000 0.9573 1.000 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.9540 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9540 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.9573 1.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.9540 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0000 0.9508 0.000 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.9508 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9573 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9540 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.9573 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9573 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.3619 0.8259 0.136 0.000 0.864
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9540 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4346 0.7682 0.184 0.816 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9573 1.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.9508 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.4974 0.6942 0.236 0.000 0.764
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9573 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9540 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9540 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0747 0.9456 0.984 0.016 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.9508 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9573 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.0000 0.9508 0.000 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.9508 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.3551 0.8304 0.132 0.000 0.868
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0000 0.9508 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.9508 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0747 0.9402 0.016 0.000 0.984
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.5650 0.5527 0.312 0.000 0.688
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.1031 0.9380 0.976 0.000 0.024
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.9540 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.9202 0.1483 0.152 0.460 0.388
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.0000 0.9508 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0000 0.9508 0.000 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9573 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9540 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9540 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9573 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0000 0.9508 0.000 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.9508 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9573 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0747 0.9402 0.016 0.000 0.984
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.9540 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.9573 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.9573 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9573 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.9540 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9573 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9573 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.9508 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.3816 0.8124 0.852 0.148 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 3 0.6168 0.3068 0.412 0.000 0.588
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.0000 0.9508 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.9540 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.9540 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9540 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.9573 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0592 0.9486 0.988 0.012 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.9573 1.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9573 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.9508 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5085 0.8157 0.836 0.092 0.072
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9540 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9573 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9540 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.9508 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.6180 0.2953 0.416 0.000 0.584
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.0000 0.9508 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.9508 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9540 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9573 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.5810 0.5027 0.336 0.000 0.664
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9573 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9573 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0747 0.9456 0.984 0.016 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9573 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5178 0.6544 0.000 0.744 0.256
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.9508 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9540 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4235 0.7675 0.824 0.000 0.176
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0237 0.9545 0.996 0.004 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.6225 0.2679 0.432 0.000 0.568
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9573 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3569 0.6800 0.196 0.804 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.5161 0.5752 0.000 0.592 0.400 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4877 0.8590 0.408 0.000 0.592 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5039 0.5773 0.000 0.592 0.404 0.004
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4996 0.7772 0.484 0.000 0.516 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3649 0.6731 0.796 0.000 0.000 0.204
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.4406 0.6720 0.000 0.700 0.300 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 4 0.7683 -0.3936 0.384 0.216 0.000 0.400
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.1389 0.4016 0.952 0.000 0.048 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.3610 0.7467 0.000 0.800 0.200 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5028 0.5797 0.000 0.596 0.400 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4998 0.0854 0.000 0.488 0.512 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.3764 0.3240 0.216 0.000 0.000 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.1557 0.6245 0.000 0.000 0.056 0.944
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4898 0.8517 0.416 0.000 0.584 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6521 0.5063 0.512 0.000 0.076 0.412
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3649 0.6731 0.796 0.000 0.000 0.204
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.5339 0.8524 0.384 0.000 0.600 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1474 0.3927 0.948 0.000 0.052 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.7816 -0.3752 0.000 0.340 0.400 0.260
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.7619 0.4317 0.208 0.000 0.436 0.356
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 4 0.5172 -0.3145 0.404 0.000 0.008 0.588
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.4761 -0.1720 0.372 0.000 0.000 0.628
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4898 0.3005 0.000 0.416 0.584 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.4630 0.3910 0.196 0.000 0.036 0.768
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0336 0.4650 0.992 0.000 0.008 0.000
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#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.5161 0.5752 0.000 0.592 0.400 0.008
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.5150 0.5794 0.000 0.596 0.396 0.008
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.5279 0.5703 0.000 0.588 0.400 0.012
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.4933 0.6315 0.568 0.000 0.000 0.432
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 4 0.4790 -0.2071 0.380 0.000 0.000 0.620
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.5387 0.5653 0.000 0.584 0.400 0.016
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.1867 0.8114 0.072 0.928 0.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.3649 0.6731 0.796 0.000 0.000 0.204
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4877 0.6569 0.592 0.000 0.000 0.408
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.3907 0.2870 0.232 0.000 0.000 0.768
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.1389 0.8282 0.000 0.952 0.048 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.4008 0.6790 0.756 0.000 0.000 0.244
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.4866 0.6590 0.596 0.000 0.000 0.404
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.4967 0.6030 0.548 0.000 0.000 0.452
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 4 0.4431 0.0373 0.304 0.000 0.000 0.696
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.4098 0.3587 0.204 0.000 0.012 0.784
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.3907 0.2870 0.232 0.000 0.000 0.768
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0188 0.8575 0.000 0.996 0.004 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.6889 0.5754 0.176 0.000 0.592 0.232
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.4866 0.8623 0.404 0.000 0.596 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.6574 0.3625 0.088 0.000 0.548 0.364
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.3908 0.6743 0.784 0.004 0.000 0.212
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.5387 0.5653 0.000 0.584 0.400 0.016
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.4998 -0.0238 0.000 0.512 0.488 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.2345 0.8103 0.000 0.900 0.100 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 4 0.4643 -0.0977 0.344 0.000 0.000 0.656
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.3649 0.3466 0.204 0.000 0.000 0.796
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 4 0.4356 0.0767 0.292 0.000 0.000 0.708
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.7143 0.5748 0.232 0.000 0.560 0.208
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.5387 0.5653 0.000 0.584 0.400 0.016
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 4 0.2921 0.4512 0.140 0.000 0.000 0.860
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 4 0.7883 -0.3277 0.292 0.000 0.328 0.380
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0188 0.4697 0.996 0.000 0.004 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.3649 0.6731 0.796 0.000 0.000 0.204
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.4866 0.8627 0.404 0.000 0.596 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.6854 0.6379 0.204 0.000 0.600 0.196
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4585 0.6764 0.668 0.000 0.000 0.332
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.4877 0.6569 0.592 0.000 0.000 0.408
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.5161 0.5752 0.000 0.592 0.400 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0336 0.4050 0.000 0.000 0.992 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.0188 0.4697 0.996 0.000 0.004 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4888 0.6536 0.588 0.000 0.000 0.412
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.0336 0.6150 0.008 0.000 0.000 0.992
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.3597 0.6420 0.836 0.000 0.016 0.148
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.6685 0.5208 0.132 0.000 0.600 0.268
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6256 0.5375 0.036 0.552 0.400 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.5692 0.5629 0.016 0.576 0.400 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.4866 0.8627 0.404 0.000 0.596 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.3942 0.6785 0.764 0.000 0.000 0.236
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0188 0.4697 0.996 0.000 0.004 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.5279 0.5703 0.000 0.588 0.400 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.5268 0.5747 0.000 0.592 0.396 0.012
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.3942 0.6101 0.000 0.764 0.236 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.2589 0.6229 0.000 0.000 0.116 0.884
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.0469 0.6127 0.012 0.000 0.000 0.988
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 4 0.6087 0.2814 0.140 0.024 0.112 0.724
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4843 0.5879 0.000 0.604 0.396 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.0000 0.6193 0.000 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5016 0.5837 0.000 0.600 0.396 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4331 0.6805 0.712 0.000 0.000 0.288
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3610 0.6716 0.800 0.000 0.000 0.200
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4907 0.8479 0.420 0.000 0.580 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.5016 0.5837 0.000 0.600 0.396 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4356 0.6804 0.708 0.000 0.000 0.292
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.4331 0.0981 0.288 0.000 0.000 0.712
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4888 0.6536 0.588 0.000 0.000 0.412
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4855 0.6150 0.000 0.000 0.400 0.600
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4989 0.5729 0.528 0.000 0.000 0.472
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4898 0.3005 0.000 0.416 0.584 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.4855 0.8652 0.400 0.000 0.600 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.8593 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4855 0.6622 0.600 0.000 0.000 0.400
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 4 0.4830 0.6153 0.000 0.000 0.392 0.608
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.5003 0.2335 0.016 0.000 0.308 0.676
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4977 0.5887 0.540 0.000 0.000 0.460
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.3143 6.01e-01 0.000 0.204 0.000 0.000 0.796
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 8.39e-01 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.6660 1.58e-01 0.000 0.392 0.000 0.380 0.228
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1768 8.11e-01 0.072 0.000 0.924 0.000 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4078 6.93e-01 0.004 0.796 0.072 0.128 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0290 6.83e-01 0.992 0.000 0.000 0.000 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 8.39e-01 0.000 0.000 1.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3274 6.77e-01 0.000 0.000 0.780 0.000 0.220
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3143 6.01e-01 0.000 0.204 0.000 0.000 0.796
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0771 6.81e-01 0.976 0.000 0.020 0.000 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.5961 5.14e-01 0.000 0.260 0.000 0.160 0.580
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.6362 -5.91e-02 0.496 0.184 0.000 0.000 0.320
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4481 1.23e-01 0.576 0.000 0.416 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.6021 4.85e-01 0.000 0.232 0.000 0.188 0.580
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.6622 2.78e-01 0.000 0.220 0.000 0.364 0.416
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.4227 6.39e-01 0.000 0.420 0.000 0.000 0.580
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 5 0.8397 3.59e-01 0.000 0.192 0.252 0.196 0.360
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.4262 6.13e-01 0.000 0.440 0.000 0.000 0.560
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.6804 -5.00e-01 0.300 0.000 0.000 0.332 0.368
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.4227 6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.5700 5.54e-01 0.176 0.000 0.000 0.628 0.196
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.4227 6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.1831 8.04e-01 0.076 0.000 0.920 0.000 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4855 5.34e-01 0.720 0.000 0.000 0.112 0.168
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0898 6.82e-01 0.972 0.000 0.020 0.000 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0162 6.83e-01 0.996 0.000 0.000 0.000 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0566 8.33e-01 0.012 0.000 0.984 0.000 0.004
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.4227 6.39e-01 0.000 0.420 0.000 0.000 0.580
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1121 6.83e-01 0.956 0.000 0.000 0.000 0.044
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.4497 9.73e-02 0.568 0.000 0.424 0.000 0.008
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#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0955 8.29e-01 0.028 0.000 0.968 0.000 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0671 6.82e-01 0.980 0.000 0.016 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4276 5.99e-01 0.716 0.000 0.028 0.000 0.256
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3689 6.72e-01 0.256 0.000 0.740 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.6715 1.37e-01 0.000 0.392 0.000 0.360 0.248
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3242 6.18e-01 0.784 0.000 0.000 0.000 0.216
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5584 5.83e-01 0.592 0.000 0.096 0.000 0.312
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.6303 1.39e-02 0.524 0.000 0.000 0.280 0.196
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3003 6.17e-01 0.812 0.000 0.000 0.000 0.188
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 6.27e-01 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3003 6.17e-01 0.812 0.000 0.000 0.000 0.188
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6161 2.52e-01 0.000 0.196 0.556 0.000 0.248
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0162 8.39e-01 0.000 0.000 0.996 0.000 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.4227 6.39e-01 0.000 0.420 0.000 0.000 0.580
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0162 6.83e-01 0.996 0.000 0.000 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 4 0.6580 -5.53e-02 0.176 0.408 0.000 0.412 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.8464 -2.41e-01 0.292 0.000 0.316 0.196 0.196
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.3196 6.11e-01 0.804 0.000 0.000 0.004 0.192
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.3659 0.4838 0.364 0.000 0.000 0.000 0.636 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.5091 0.1635 0.000 0.080 0.000 0.416 0.504 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4503 0.5300 0.232 0.000 0.684 0.000 0.000 0.084
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0146 0.8878 0.000 0.996 0.004 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3684 0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0146 0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3883 0.4567 0.332 0.000 0.656 0.000 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0000 0.8353 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3684 0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.0508 0.8387 0.000 0.012 0.000 0.004 0.984 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.4821 0.2086 0.416 0.016 0.000 0.000 0.540 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1700 0.7858 0.000 0.004 0.000 0.916 0.000 0.080
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5193 0.2988 0.552 0.000 0.344 0.000 0.000 0.104
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0622 0.8371 0.000 0.012 0.000 0.008 0.980 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.4095 0.1124 0.000 0.008 0.000 0.480 0.512 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.5515 0.1384 0.000 0.000 0.136 0.492 0.372 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.1663 0.7839 0.000 0.088 0.000 0.000 0.912 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.4105 0.4661 0.348 0.000 0.000 0.020 0.000 0.632
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.0458 0.8384 0.000 0.016 0.000 0.000 0.984 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.2996 0.6708 0.000 0.000 0.000 0.228 0.000 0.772
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4226 0.5924 0.152 0.000 0.736 0.000 0.000 0.112
#> EE97212E-8D5D-4548-8DD2-317049601FDB 6 0.3183 0.5889 0.128 0.004 0.000 0.040 0.000 0.828
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3998 0.3832 0.504 0.000 0.004 0.000 0.000 0.492
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3659 0.5377 0.636 0.000 0.000 0.000 0.000 0.364
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0551 0.8336 0.004 0.004 0.984 0.000 0.000 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.3971 0.3801 0.548 0.004 0.000 0.000 0.000 0.448
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.4972 0.2792 0.568 0.000 0.352 0.000 0.000 0.080
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.4527 0.5637 0.000 0.236 0.000 0.680 0.000 0.084
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3280 0.7494 0.004 0.808 0.000 0.160 0.000 0.028
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.3388 0.6505 0.000 0.000 0.792 0.036 0.000 0.172
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2969 0.6728 0.000 0.000 0.000 0.224 0.000 0.776
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3647 0.5311 0.640 0.000 0.000 0.000 0.000 0.360
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 6 0.1957 0.5990 0.112 0.000 0.000 0.000 0.000 0.888
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0260 0.8882 0.000 0.992 0.000 0.000 0.008 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.4486 0.4008 0.396 0.000 0.000 0.016 0.012 0.576
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.4765 0.5484 0.012 0.244 0.000 0.672 0.000 0.072
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6082 -0.0513 0.000 0.000 0.368 0.272 0.360 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.4573 0.4785 0.324 0.004 0.004 0.028 0.004 0.636
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3463 0.5255 0.840 0.040 0.088 0.000 0.012 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.4017 0.6395 0.160 0.004 0.000 0.076 0.000 0.760
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.5746 -0.0597 0.376 0.000 0.452 0.000 0.000 0.172
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.4103 0.0741 0.004 0.004 0.000 0.544 0.448 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5412 0.1967 0.496 0.000 0.384 0.000 0.000 0.120
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.1814 0.7223 0.000 0.000 0.000 0.100 0.000 0.900
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.6178 0.2170 0.336 0.000 0.000 0.264 0.004 0.396
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3717 0.3965 0.000 0.616 0.000 0.384 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.4263 0.3908 0.376 0.000 0.600 0.000 0.000 0.024
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.2980 0.6842 0.000 0.012 0.000 0.180 0.808 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3867 0.3932 0.512 0.000 0.000 0.000 0.000 0.488
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2823 0.7191 0.000 0.796 0.000 0.204 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.2003 0.7223 0.000 0.000 0.000 0.116 0.000 0.884
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.3843 0.4349 0.548 0.000 0.000 0.000 0.000 0.452
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.4127 0.3864 0.364 0.000 0.620 0.000 0.012 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.3390 0.5767 0.296 0.000 0.000 0.000 0.704 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2805 0.4613 0.828 0.000 0.000 0.000 0.012 0.160
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 6 0.1970 0.6149 0.092 0.000 0.008 0.000 0.000 0.900
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.2191 0.7220 0.000 0.004 0.000 0.120 0.000 0.876
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 5 0.3866 0.1045 0.000 0.000 0.000 0.484 0.516 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.4293 0.3974 0.396 0.584 0.000 0.000 0.016 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.5064 0.4625 0.000 0.000 0.152 0.216 0.632 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3483 0.6693 0.212 0.024 0.764 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.2815 0.7367 0.032 0.120 0.000 0.000 0.848 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.5181 0.1232 0.088 0.484 0.000 0.000 0.000 0.428
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 6 0.2527 0.5370 0.168 0.000 0.000 0.000 0.000 0.832
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0146 0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.2762 0.6907 0.000 0.000 0.000 0.196 0.000 0.804
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.2048 0.7218 0.000 0.000 0.000 0.120 0.000 0.880
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 6 0.2101 0.7224 0.004 0.004 0.000 0.100 0.000 0.892
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 6 0.3670 0.6213 0.152 0.004 0.000 0.056 0.000 0.788
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.5659 0.0951 0.448 0.004 0.416 0.000 0.000 0.132
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 6 0.4506 0.4422 0.176 0.120 0.000 0.000 0.000 0.704
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.3819 0.5232 0.624 0.004 0.000 0.000 0.000 0.372
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.0146 0.8338 0.004 0.000 0.000 0.000 0.996 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 5 0.5421 0.0514 0.000 0.116 0.000 0.432 0.452 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0713 0.8792 0.000 0.972 0.000 0.000 0.028 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 6 0.3838 0.6684 0.116 0.004 0.000 0.096 0.000 0.784
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 6 0.1958 0.7224 0.000 0.004 0.000 0.100 0.000 0.896
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 5 0.3975 0.3351 0.000 0.392 0.008 0.000 0.600 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 6 0.1958 0.7224 0.000 0.004 0.000 0.100 0.000 0.896
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5349 0.3024 0.356 0.000 0.548 0.084 0.012 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.0632 0.8258 0.000 0.000 0.024 0.976 0.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.5516 0.2650 0.504 0.000 0.356 0.000 0.000 0.140
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.3620 0.4275 0.000 0.648 0.000 0.000 0.352 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 6 0.4555 0.4020 0.392 0.000 0.000 0.020 0.012 0.576
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 5 0.7279 0.1797 0.000 0.160 0.000 0.208 0.432 0.200
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.2378 0.7770 0.000 0.848 0.000 0.152 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.1082 0.5662 0.956 0.000 0.000 0.000 0.004 0.040
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 4 0.4855 -0.0318 0.000 0.056 0.000 0.484 0.460 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.1367 0.5481 0.944 0.000 0.044 0.000 0.012 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1074 0.8774 0.000 0.960 0.000 0.028 0.012 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0146 0.8379 0.000 0.004 0.996 0.000 0.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.3898 0.1535 0.652 0.000 0.000 0.000 0.012 0.336
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.4122 0.0714 0.000 0.004 0.520 0.004 0.000 0.472
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 6 0.2003 0.7223 0.000 0.000 0.000 0.116 0.000 0.884
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0291 0.8885 0.000 0.992 0.000 0.004 0.004 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.4368 0.3240 0.672 0.000 0.272 0.000 0.056 0.000
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#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0547 0.8786 0.000 0.980 0.020 0.000 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0858 0.8792 0.000 0.968 0.000 0.028 0.004 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 6 0.2300 0.5672 0.144 0.000 0.000 0.000 0.000 0.856
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.2320 0.7581 0.132 0.000 0.864 0.000 0.000 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 6 0.4407 0.4305 0.364 0.000 0.000 0.016 0.012 0.608
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 6 0.1501 0.6337 0.076 0.000 0.000 0.000 0.000 0.924
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.5258 0.2740 0.092 0.004 0.540 0.000 0.000 0.364
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 5 0.5479 0.0475 0.000 0.124 0.000 0.428 0.448 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 6 0.1471 0.7132 0.000 0.004 0.000 0.064 0.000 0.932
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.5852 -0.1159 0.484 0.004 0.120 0.000 0.012 0.380
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.2135 0.7205 0.000 0.000 0.000 0.128 0.000 0.872
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0632 0.8813 0.000 0.976 0.000 0.000 0.024 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 6 0.2048 0.7222 0.000 0.000 0.000 0.120 0.000 0.880
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1151 0.5645 0.956 0.000 0.000 0.000 0.012 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1225 0.5639 0.952 0.000 0.000 0.000 0.012 0.036
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.3789 0.3501 0.416 0.000 0.584 0.000 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.8385 0.000 0.000 1.000 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.2933 0.6498 0.000 0.004 0.796 0.000 0.000 0.200
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.3695 0.5293 0.624 0.000 0.000 0.000 0.000 0.376
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3774 0.4914 0.592 0.000 0.000 0.000 0.000 0.408
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0260 0.8872 0.000 0.992 0.000 0.008 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 4 0.4118 0.4621 0.000 0.028 0.312 0.660 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.1511 0.5480 0.940 0.004 0.044 0.000 0.012 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0692 0.8316 0.004 0.020 0.976 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 6 0.2730 0.4992 0.192 0.000 0.000 0.000 0.000 0.808
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0000 0.8353 0.000 0.000 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.2092 0.7216 0.000 0.000 0.000 0.124 0.000 0.876
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.3672 0.5336 0.632 0.000 0.000 0.000 0.000 0.368
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.1814 0.7223 0.000 0.000 0.000 0.100 0.000 0.900
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 6 0.3807 0.3289 0.000 0.004 0.368 0.000 0.000 0.628
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.6270 0.2657 0.352 0.228 0.000 0.408 0.012 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.2178 0.7327 0.000 0.000 0.000 0.868 0.000 0.132
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.1075 0.8124 0.000 0.000 0.000 0.952 0.000 0.048
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.2048 0.7218 0.000 0.000 0.000 0.120 0.000 0.880
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.5841 0.1101 0.192 0.000 0.000 0.372 0.436 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.1910 0.7226 0.000 0.000 0.000 0.108 0.000 0.892
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.1910 0.7226 0.000 0.000 0.000 0.108 0.000 0.892
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3907 0.3612 0.408 0.004 0.588 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.2121 0.5019 0.892 0.000 0.000 0.000 0.012 0.096
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2274 0.5429 0.892 0.000 0.088 0.000 0.012 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.1814 0.7367 0.000 0.000 0.000 0.900 0.100 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.2527 0.6964 0.000 0.000 0.000 0.168 0.832 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0146 0.8894 0.000 0.996 0.000 0.000 0.004 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.3329 0.6578 0.004 0.004 0.000 0.236 0.000 0.756
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.2843 0.7149 0.000 0.000 0.036 0.116 0.000 0.848
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.3383 0.4656 0.268 0.004 0.000 0.000 0.000 0.728
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.2309 0.8124 0.028 0.888 0.000 0.000 0.000 0.084
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2823 0.7191 0.000 0.796 0.000 0.204 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.2135 0.7205 0.000 0.000 0.000 0.128 0.000 0.872
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.3967 0.4019 0.000 0.012 0.000 0.356 0.632 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1334 0.8171 0.032 0.000 0.948 0.000 0.000 0.020
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3684 0.5314 0.628 0.000 0.000 0.000 0.000 0.372
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1349 0.5405 0.940 0.000 0.000 0.000 0.056 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.5136 0.1388 0.420 0.000 0.496 0.000 0.000 0.084
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 5 0.5414 0.0983 0.000 0.116 0.000 0.416 0.468 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 6 0.3805 0.3318 0.328 0.004 0.000 0.000 0.004 0.664
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5419 0.3171 0.636 0.004 0.184 0.000 0.012 0.164
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.4185 0.6358 0.168 0.004 0.000 0.084 0.000 0.744
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.2527 0.5350 0.168 0.000 0.000 0.000 0.000 0.832
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.8398 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 6 0.2664 0.5099 0.184 0.000 0.000 0.000 0.000 0.816
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.3747 0.3592 0.000 0.000 0.604 0.000 0.396 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0146 0.8384 0.004 0.000 0.996 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.0363 0.8404 0.000 0.012 0.000 0.000 0.988 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3563 0.5500 0.664 0.000 0.000 0.000 0.000 0.336
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.5698 0.1094 0.016 0.500 0.000 0.108 0.000 0.376
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.4241 0.6123 0.004 0.004 0.164 0.080 0.000 0.748
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.2178 0.5824 0.132 0.000 0.000 0.000 0.000 0.868
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.406 0.695 0.869 0.4811 0.506 0.506
#> 3 3 0.355 0.453 0.716 0.3368 0.707 0.494
#> 4 4 0.537 0.565 0.781 0.1330 0.814 0.539
#> 5 5 0.546 0.491 0.696 0.0626 0.833 0.492
#> 6 6 0.615 0.562 0.734 0.0451 0.870 0.522
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.7453 0.68209 0.212 0.788
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.8016 0.61032 0.756 0.244
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.7453 0.71511 0.212 0.788
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.8608 0.56037 0.284 0.716
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.8608 0.56037 0.284 0.716
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.8443 0.54847 0.728 0.272
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.8144 0.68912 0.252 0.748
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.83597 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.7883 0.69749 0.236 0.764
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.8608 0.53111 0.716 0.284
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.8661 0.56026 0.288 0.712
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.83597 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0376 0.82534 0.004 0.996
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.2778 0.81360 0.952 0.048
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.1414 0.82970 0.980 0.020
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.8661 0.52173 0.712 0.288
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.8861 0.53230 0.696 0.304
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.6887 0.70498 0.184 0.816
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.8608 0.56037 0.284 0.716
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0376 0.82534 0.004 0.996
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.7376 0.68563 0.208 0.792
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0376 0.82534 0.004 0.996
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.83597 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0672 0.82734 0.008 0.992
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1414 0.82970 0.980 0.020
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0376 0.82534 0.004 0.996
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.8081 0.58749 0.752 0.248
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.1843 0.82426 0.972 0.028
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0376 0.83541 0.996 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0376 0.83541 0.996 0.004
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#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0376 0.83541 0.996 0.004
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.83597 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.83597 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.9983 -0.03519 0.524 0.476
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.8608 0.63973 0.284 0.716
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.9909 0.23731 0.556 0.444
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0376 0.83541 0.996 0.004
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0672 0.83299 0.992 0.008
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0672 0.82830 0.008 0.992
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0938 0.83218 0.988 0.012
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.1414 0.83011 0.980 0.020
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0376 0.83541 0.996 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0376 0.83526 0.996 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.9983 -0.04652 0.524 0.476
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.4431 0.78060 0.908 0.092
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0376 0.83541 0.996 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.3879 0.80208 0.076 0.924
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.7453 0.65027 0.788 0.212
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.1633 0.82559 0.024 0.976
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0376 0.82534 0.004 0.996
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0376 0.83541 0.996 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0672 0.82830 0.008 0.992
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.8499 0.54146 0.724 0.276
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.7815 0.69633 0.232 0.768
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0672 0.83299 0.992 0.008
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0938 0.82888 0.012 0.988
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.9866 0.26670 0.568 0.432
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0376 0.83541 0.996 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.9996 0.13812 0.488 0.512
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0938 0.82888 0.012 0.988
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.8608 0.56037 0.284 0.716
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0376 0.83541 0.996 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0376 0.83541 0.996 0.004
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0672 0.83299 0.992 0.008
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0672 0.83299 0.992 0.008
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0938 0.82888 0.012 0.988
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0938 0.82888 0.012 0.988
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.9909 0.23731 0.556 0.444
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.8661 0.52173 0.712 0.288
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.9993 -0.07083 0.516 0.484
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.83597 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.9996 0.16660 0.488 0.512
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0672 0.83339 0.992 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.9988 -0.06273 0.520 0.480
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.7815 0.69601 0.232 0.768
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.8499 0.54146 0.724 0.276
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0376 0.83541 0.996 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.83597 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.5408 0.76816 0.124 0.876
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.1843 0.82749 0.028 0.972
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.1843 0.82216 0.972 0.028
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.7528 0.71114 0.216 0.784
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0376 0.83541 0.996 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0376 0.82534 0.004 0.996
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0938 0.82888 0.012 0.988
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0938 0.83282 0.988 0.012
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.83597 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.8661 0.52173 0.712 0.288
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.83597 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.8661 0.52869 0.712 0.288
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.8608 0.56037 0.284 0.716
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.7528 0.64441 0.784 0.216
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.7815 0.62420 0.768 0.232
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0376 0.83541 0.996 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9522 0.40994 0.628 0.372
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0672 0.83299 0.992 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0376 0.83541 0.996 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.8813 0.49265 0.700 0.300
#> 1122039D-5785-4F70-9916-17C585453512 1 0.9661 0.36699 0.608 0.392
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0376 0.83541 0.996 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.83597 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.8608 0.56037 0.284 0.716
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.8608 0.56037 0.284 0.716
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0672 0.82830 0.008 0.992
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0672 0.83443 0.992 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.5629 0.75755 0.868 0.132
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0376 0.83541 0.996 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.83597 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.7950 0.68784 0.240 0.760
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.7745 0.70068 0.228 0.772
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.8386 0.60250 0.268 0.732
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0938 0.83261 0.988 0.012
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.9988 0.13250 0.520 0.480
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0376 0.83541 0.996 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0376 0.83541 0.996 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0672 0.83371 0.992 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.8499 0.54146 0.724 0.276
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0376 0.82534 0.004 0.996
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.83597 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.83597 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.83597 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0376 0.83541 0.996 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.9909 0.23731 0.556 0.444
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0376 0.83541 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0938 0.82888 0.012 0.988
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.7815 0.69618 0.232 0.768
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0938 0.82888 0.012 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.83597 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.9732 0.31305 0.596 0.404
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0376 0.83541 0.996 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.83597 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5733 0.6123 0.000 0.676 0.324
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.5178 0.5152 0.744 0.256 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.6302 -0.2710 0.000 0.480 0.520
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.8608 -0.0650 0.412 0.488 0.100
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.6309 0.0411 0.504 0.496 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0237 0.5159 0.000 0.004 0.996
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5845 0.5362 0.004 0.688 0.308
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.6521 0.3612 0.496 0.004 0.500
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.7944 0.4468 0.072 0.580 0.348
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.5145 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.5560 0.4885 0.000 0.700 0.300
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.5115 0.5352 0.228 0.004 0.768
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2878 0.7325 0.096 0.904 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.6664 0.3755 0.464 0.008 0.528
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.5740 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.2945 0.5381 0.088 0.004 0.908
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.5138 0.5196 0.748 0.252 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.5608 0.6676 0.120 0.808 0.072
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.6309 0.0411 0.504 0.496 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0237 0.7819 0.000 0.996 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.9070 -0.2175 0.428 0.136 0.436
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.4346 0.6174 0.184 0.816 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.4931 0.3416 0.784 0.004 0.212
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0237 0.7812 0.004 0.996 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0747 0.5699 0.984 0.000 0.016
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.3116 0.7486 0.000 0.892 0.108
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3918 0.5423 0.140 0.004 0.856
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.7075 -0.3594 0.496 0.020 0.484
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5024 0.5341 0.220 0.004 0.776
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.6298 0.4543 0.388 0.004 0.608
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.7742 0.2384 0.080 0.288 0.632
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0237 0.7819 0.000 0.996 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.5859 0.4026 0.656 0.344 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.6500 0.3789 0.464 0.004 0.532
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4868 0.4903 0.100 0.056 0.844
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.6962 0.5531 0.724 0.184 0.092
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.9921 -0.1665 0.308 0.396 0.296
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6451 0.0263 0.560 0.004 0.436
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0747 0.5699 0.984 0.000 0.016
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.8996 0.2505 0.504 0.356 0.140
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.6386 0.4123 0.412 0.004 0.584
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.6224 0.5055 0.296 0.016 0.688
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.7827 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3192 0.4823 0.888 0.000 0.112
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6057 0.4179 0.656 0.340 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.5145 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.4974 0.6694 0.000 0.764 0.236
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.9320 -0.0401 0.496 0.320 0.184
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.5109 0.5364 0.212 0.008 0.780
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.8204 0.1869 0.316 0.588 0.096
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.6291 0.3752 0.468 0.000 0.532
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4682 0.5382 0.192 0.004 0.804
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.6225 0.1053 0.432 0.568 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.3500 0.5399 0.116 0.004 0.880
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.6521 -0.3643 0.500 0.004 0.496
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.3879 0.4252 0.848 0.000 0.152
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.7827 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6243 0.6004 0.124 0.776 0.100
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.3879 0.4435 0.000 0.152 0.848
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.8094 0.3002 0.288 0.612 0.100
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.5754 0.5061 0.296 0.004 0.700
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.7827 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.9320 -0.0399 0.496 0.320 0.184
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.6521 0.3612 0.496 0.004 0.500
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.9223 0.2824 0.172 0.324 0.504
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0424 0.5113 0.000 0.008 0.992
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.1411 0.7769 0.000 0.964 0.036
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.6521 0.3612 0.496 0.004 0.500
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.5588 0.5151 0.276 0.004 0.720
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3551 0.4805 0.868 0.000 0.132
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.6587 0.1073 0.424 0.568 0.008
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.8979 0.1114 0.128 0.420 0.452
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.7827 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.3619 0.7339 0.000 0.864 0.136
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3412 0.4318 0.000 0.124 0.876
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.8568 0.4463 0.608 0.192 0.200
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#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.5138 0.5196 0.748 0.252 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.6521 0.3612 0.496 0.004 0.500
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.9868 0.2634 0.260 0.344 0.396
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.4346 0.7070 0.000 0.816 0.184
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.5416 0.6761 0.080 0.820 0.100
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.6521 0.3612 0.496 0.004 0.500
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.5145 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.5291 0.5162 0.268 0.000 0.732
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.3267 0.4986 0.884 0.000 0.116
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.7827 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0237 0.7819 0.000 0.996 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.5859 0.4026 0.656 0.344 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.5145 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 2 0.9563 0.0249 0.284 0.480 0.236
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.4178 0.4618 0.172 0.000 0.828
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.5621 0.1312 0.000 0.308 0.692
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.6432 0.4068 0.428 0.004 0.568
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0892 0.5068 0.000 0.020 0.980
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.6215 -0.1581 0.000 0.428 0.572
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.9722 0.2938 0.244 0.312 0.444
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.5024 0.5341 0.220 0.004 0.776
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.6521 0.3612 0.496 0.004 0.500
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.6095 0.2096 0.392 0.608 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0892 0.7795 0.000 0.980 0.020
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.5541 0.5237 0.252 0.008 0.740
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.6008 0.5233 0.000 0.628 0.372
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.5754 0.5061 0.296 0.004 0.700
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.6888 0.0975 0.432 0.552 0.016
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.7827 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.4555 0.3704 0.800 0.000 0.200
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.6398 0.4145 0.416 0.004 0.580
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.5145 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.6521 0.3612 0.496 0.004 0.500
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.9575 0.2954 0.216 0.320 0.464
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.8425 0.1258 0.348 0.552 0.100
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0237 0.5750 0.996 0.004 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.4605 0.5666 0.796 0.204 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4784 0.3645 0.796 0.004 0.200
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.6180 0.3057 0.584 0.416 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.3412 0.4898 0.876 0.000 0.124
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.6359 0.3882 0.404 0.004 0.592
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.5145 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.9270 0.3252 0.520 0.280 0.200
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 3 0.5690 0.5106 0.288 0.004 0.708
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.4555 0.4409 0.200 0.000 0.800
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.6309 0.0411 0.504 0.496 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.6438 0.6106 0.136 0.764 0.100
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.7827 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.8052 0.1838 0.652 0.152 0.196
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.4555 0.4126 0.800 0.000 0.200
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5722 0.5083 0.292 0.004 0.704
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.6521 0.3612 0.496 0.004 0.500
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.6168 -0.1195 0.000 0.412 0.588
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.7918 0.3993 0.256 0.640 0.104
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2959 0.7186 0.000 0.900 0.100
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.4399 0.3907 0.812 0.000 0.188
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.8442 0.4043 0.548 0.352 0.100
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0424 0.5167 0.008 0.000 0.992
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.6432 0.4068 0.428 0.004 0.568
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.4974 0.4316 0.236 0.000 0.764
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1163 0.5209 0.028 0.000 0.972
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1289 0.7669 0.032 0.968 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.6521 0.3612 0.496 0.004 0.500
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.6286 0.3790 0.464 0.000 0.536
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.6521 0.3612 0.496 0.004 0.500
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.6521 0.3612 0.496 0.004 0.500
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.5835 0.4091 0.660 0.340 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.6148 0.4755 0.356 0.004 0.640
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0237 0.7819 0.000 0.996 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.6215 -0.1581 0.000 0.428 0.572
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.7827 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.6521 0.3612 0.496 0.004 0.500
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.8260 0.3684 0.192 0.636 0.172
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.9623 0.3005 0.232 0.304 0.464
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.6521 0.3612 0.496 0.004 0.500
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.7485 0.55928 0.164 0.560 0.260 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.1174 0.80750 0.012 0.020 0.000 0.968
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.5656 0.01660 0.012 0.384 0.592 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1635 0.79822 0.044 0.008 0.000 0.948
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.3837 0.68907 0.000 0.224 0.000 0.776
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4972 -0.10214 0.456 0.000 0.544 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.7692 0.46120 0.048 0.248 0.580 0.124
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0188 0.64280 0.996 0.000 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.7009 0.59522 0.164 0.628 0.192 0.016
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.5320 0.34853 0.572 0.000 0.416 0.012
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.5986 0.57090 0.276 0.656 0.064 0.004
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4500 0.40844 0.684 0.000 0.316 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2921 0.74430 0.000 0.860 0.000 0.140
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.2188 0.64188 0.936 0.020 0.032 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1022 0.80385 0.032 0.000 0.000 0.968
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4193 0.50455 0.732 0.000 0.268 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.1174 0.80750 0.012 0.020 0.000 0.968
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.7292 0.17489 0.152 0.460 0.000 0.388
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.4380 0.69368 0.164 0.032 0.004 0.800
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.1109 0.81138 0.000 0.968 0.028 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4389 0.54114 0.000 0.116 0.812 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3969 0.67088 0.000 0.804 0.016 0.180
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.5728 0.13902 0.600 0.000 0.036 0.364
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1109 0.81138 0.000 0.968 0.028 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.4790 0.43519 0.380 0.000 0.000 0.620
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.3390 0.77630 0.000 0.852 0.132 0.016
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3837 0.58365 0.224 0.000 0.776 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.1297 0.63577 0.964 0.020 0.000 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.4605 0.46930 0.336 0.000 0.664 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0921 0.64062 0.972 0.000 0.028 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4831 0.59887 0.188 0.024 0.772 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1109 0.81138 0.000 0.968 0.028 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.1022 0.80533 0.000 0.032 0.000 0.968
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1452 0.64257 0.956 0.000 0.036 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.5068 0.43960 0.676 0.004 0.308 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.2973 0.78214 0.096 0.020 0.000 0.884
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.7462 0.51030 0.244 0.172 0.568 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.5352 0.51279 0.388 0.000 0.596 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.4790 0.43519 0.380 0.000 0.000 0.620
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.1022 0.80533 0.000 0.032 0.000 0.968
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.2704 0.61383 0.876 0.000 0.124 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.5580 0.49727 0.408 0.016 0.572 0.004
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0188 0.81487 0.000 0.996 0.004 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.5713 0.14979 0.604 0.000 0.036 0.360
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.5073 0.70579 0.056 0.200 0.000 0.744
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1637 0.60137 0.060 0.000 0.940 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.4661 0.70013 0.000 0.728 0.256 0.016
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5646 0.14389 0.592 0.384 0.008 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.5560 0.33510 0.392 0.024 0.584 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.8132 -0.16233 0.192 0.420 0.020 0.368
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.1610 0.64176 0.952 0.000 0.032 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4331 0.55897 0.288 0.000 0.712 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.3444 0.72624 0.000 0.184 0.000 0.816
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.4843 0.30876 0.604 0.000 0.396 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.5511 0.38545 0.484 0.000 0.500 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.5028 0.06303 0.596 0.000 0.004 0.400
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3471 0.76665 0.072 0.868 0.000 0.060
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5814 0.37865 0.620 0.024 0.344 0.012
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 4 0.5865 0.34738 0.036 0.412 0.000 0.552
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3688 0.47156 0.792 0.000 0.208 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.5754 0.26041 0.428 0.548 0.008 0.016
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0336 0.64342 0.992 0.000 0.008 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.5934 0.34711 0.376 0.024 0.588 0.012
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.2255 0.59742 0.068 0.000 0.920 0.012
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5302 0.67841 0.164 0.752 0.080 0.004
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.1118 0.63864 0.964 0.000 0.036 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.5310 0.49547 0.412 0.000 0.576 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.6031 0.44149 0.420 0.000 0.536 0.044
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5361 0.52257 0.004 0.344 0.016 0.636
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.7006 0.32836 0.328 0.136 0.536 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0188 0.81523 0.000 0.996 0.004 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.3647 0.76651 0.000 0.832 0.152 0.016
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.7076 -0.10057 0.404 0.088 0.496 0.012
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0657 0.80588 0.004 0.000 0.012 0.984
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2131 0.60022 0.032 0.036 0.932 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.4630 0.68234 0.196 0.768 0.036 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.5238 0.59175 0.204 0.040 0.744 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1792 0.60143 0.068 0.000 0.932 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.5643 0.47620 0.428 0.024 0.548 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.1489 0.81226 0.000 0.952 0.044 0.004
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.64210 1.000 0.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.4353 0.70273 0.000 0.756 0.232 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 4 0.4382 0.57264 0.296 0.000 0.000 0.704
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 4 0.4898 0.36636 0.416 0.000 0.000 0.584
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.2495 0.59489 0.028 0.036 0.924 0.012
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.5483 0.44709 0.448 0.000 0.536 0.016
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0657 0.81438 0.012 0.984 0.004 0.000
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#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.2335 0.79696 0.060 0.020 0.000 0.920
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.4776 0.37748 0.000 0.376 0.624 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.5244 0.47566 0.436 0.000 0.556 0.008
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.4746 0.32619 0.000 0.632 0.368 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.5231 0.36166 0.604 0.000 0.384 0.012
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.5645 0.58354 0.020 0.640 0.328 0.012
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.5906 0.32353 0.436 0.000 0.036 0.528
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0592 0.80728 0.016 0.000 0.000 0.984
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.5273 0.44733 0.456 0.000 0.536 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.6656 0.51790 0.348 0.068 0.572 0.012
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.4327 0.72655 0.000 0.768 0.216 0.016
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4549 0.69397 0.036 0.776 0.000 0.188
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.5167 0.08842 0.644 0.000 0.340 0.016
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.1940 0.60116 0.076 0.000 0.924 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.5535 -0.20146 0.560 0.000 0.420 0.020
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.4500 0.53930 0.316 0.000 0.000 0.684
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0817 0.81246 0.000 0.976 0.024 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.1022 0.80533 0.000 0.032 0.000 0.968
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.1867 0.60073 0.072 0.000 0.928 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 2 0.8030 0.02305 0.344 0.444 0.196 0.016
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.5110 0.39730 0.636 0.000 0.352 0.012
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.2179 0.59855 0.064 0.000 0.924 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2647 0.61112 0.880 0.000 0.120 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.5231 0.36166 0.604 0.000 0.384 0.012
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.2032 0.59908 0.028 0.036 0.936 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.5959 0.51729 0.384 0.024 0.580 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4624 0.37330 0.660 0.000 0.340 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3074 0.52055 0.848 0.000 0.152 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.7304 0.18177 0.156 0.528 0.004 0.312
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.1022 0.80793 0.000 0.968 0.000 0.032
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3528 0.57254 0.808 0.000 0.192 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.5391 0.54000 0.004 0.604 0.380 0.012
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.4925 0.49277 0.428 0.000 0.572 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 4 0.7318 0.58952 0.164 0.184 0.032 0.620
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0188 0.81523 0.000 0.996 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.5483 0.44709 0.448 0.000 0.536 0.016
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.2704 0.60898 0.876 0.000 0.124 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.5366 -0.08537 0.440 0.000 0.548 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.3790 0.49994 0.820 0.000 0.164 0.016
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.6152 0.53693 0.336 0.036 0.612 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.8261 0.00540 0.164 0.440 0.036 0.360
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0592 0.80728 0.016 0.000 0.000 0.984
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0592 0.80728 0.016 0.000 0.000 0.984
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.5673 0.43954 0.448 0.000 0.528 0.024
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.6712 0.60161 0.164 0.200 0.004 0.632
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.4907 -0.00690 0.580 0.000 0.000 0.420
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.5417 0.49250 0.412 0.000 0.572 0.016
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5189 0.37033 0.616 0.000 0.372 0.012
#> 1122039D-5785-4F70-9916-17C585453512 4 0.1174 0.80581 0.000 0.020 0.012 0.968
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4961 -0.18705 0.552 0.000 0.448 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.5110 0.39766 0.636 0.000 0.352 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3688 0.70070 0.000 0.208 0.000 0.792
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.7702 0.18855 0.196 0.452 0.004 0.348
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0804 0.81516 0.008 0.980 0.012 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.6703 0.29771 0.612 0.232 0.000 0.156
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0657 0.80588 0.004 0.000 0.012 0.984
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5408 0.49660 0.408 0.000 0.576 0.016
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0336 0.64130 0.992 0.000 0.000 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2495 0.59489 0.028 0.036 0.924 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4980 0.52823 0.304 0.680 0.016 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1118 0.80326 0.036 0.964 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.4961 0.27987 0.448 0.000 0.000 0.552
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.5398 0.65766 0.200 0.064 0.004 0.732
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.5273 -0.10796 0.456 0.000 0.536 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2589 0.61159 0.884 0.000 0.116 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.5143 0.40739 0.628 0.000 0.360 0.012
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4998 -0.14268 0.488 0.000 0.512 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1557 0.79489 0.000 0.944 0.000 0.056
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0524 0.64194 0.988 0.000 0.004 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.1557 0.64176 0.944 0.000 0.056 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0592 0.63869 0.984 0.000 0.000 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3266 0.50370 0.832 0.000 0.168 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.1022 0.80533 0.000 0.032 0.000 0.968
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3528 0.48189 0.808 0.000 0.192 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2495 0.59489 0.028 0.036 0.924 0.012
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.81510 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0336 0.64342 0.992 0.000 0.008 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.6955 0.35840 0.296 0.560 0.144 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5313 0.51978 0.376 0.000 0.608 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0188 0.64176 0.996 0.000 0.000 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 3 0.6611 -0.43240 0.048 0.420 0.456 0.000 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.6587 0.39674 0.000 0.220 0.444 0.000 0.336
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.2605 0.72032 0.148 0.000 0.000 0.852 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.4626 0.44993 0.000 0.364 0.020 0.616 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 5 0.2020 0.45146 0.000 0.000 0.100 0.000 0.900
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.6799 0.08649 0.036 0.516 0.360 0.024 0.064
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 5 0.4304 0.19230 0.484 0.000 0.000 0.000 0.516
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.7998 0.16721 0.172 0.440 0.244 0.000 0.144
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.3276 0.39784 0.032 0.000 0.132 0.000 0.836
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.7850 0.43963 0.128 0.448 0.272 0.000 0.152
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 5 0.4141 0.57717 0.236 0.000 0.028 0.000 0.736
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1907 0.73181 0.000 0.928 0.028 0.044 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4912 -0.13647 0.500 0.012 0.008 0.000 0.480
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1270 0.81674 0.052 0.000 0.000 0.948 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 5 0.1701 0.49608 0.048 0.000 0.016 0.000 0.936
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 4 0.7909 -0.04931 0.108 0.392 0.056 0.400 0.044
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.3267 0.78246 0.024 0.044 0.000 0.868 0.064
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.3636 0.66383 0.000 0.728 0.272 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.5183 0.31602 0.000 0.024 0.708 0.204 0.064
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3531 0.64536 0.000 0.816 0.036 0.148 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2685 0.65031 0.880 0.000 0.092 0.000 0.028
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.3550 0.67800 0.004 0.760 0.236 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3109 0.61690 0.800 0.000 0.000 0.200 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.3983 0.62416 0.000 0.660 0.340 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 5 0.5793 0.01290 0.100 0.000 0.364 0.000 0.536
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.1168 0.68238 0.960 0.008 0.000 0.000 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 5 0.6000 0.25205 0.160 0.000 0.268 0.000 0.572
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 5 0.4182 0.28098 0.400 0.000 0.000 0.000 0.600
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.6418 0.37466 0.316 0.004 0.508 0.000 0.172
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.3636 0.66383 0.000 0.728 0.272 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 5 0.4304 0.14155 0.484 0.000 0.000 0.000 0.516
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.2416 0.56298 0.100 0.000 0.012 0.000 0.888
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4235 0.16036 0.576 0.000 0.000 0.424 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5617 0.43472 0.620 0.124 0.256 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4410 0.19190 0.556 0.000 0.440 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3074 0.61904 0.804 0.000 0.000 0.196 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 5 0.3999 0.47456 0.344 0.000 0.000 0.000 0.656
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.5701 0.34100 0.580 0.004 0.328 0.000 0.088
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1043 0.74208 0.000 0.960 0.040 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3539 0.63775 0.848 0.000 0.092 0.032 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6813 -0.11282 0.360 0.332 0.000 0.308 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4126 0.54250 0.000 0.000 0.620 0.000 0.380
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.5650 -0.42716 0.000 0.460 0.464 0.000 0.076
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.2554 0.66441 0.892 0.036 0.000 0.000 0.072
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.6306 0.18067 0.172 0.000 0.328 0.000 0.500
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.7637 0.23421 0.108 0.536 0.048 0.252 0.056
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2127 0.65931 0.892 0.000 0.000 0.000 0.108
#> 4379559E-E467-49BD-9673-40A486146A3B 5 0.6244 0.07039 0.156 0.000 0.348 0.000 0.496
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.3081 0.75015 0.000 0.156 0.012 0.832 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 5 0.2754 0.49102 0.040 0.000 0.080 0.000 0.880
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1357 0.68320 0.948 0.000 0.048 0.000 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.4543 0.61897 0.768 0.000 0.008 0.120 0.104
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0290 0.73924 0.000 0.992 0.008 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4413 0.57184 0.232 0.724 0.000 0.044 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 5 0.1522 0.51818 0.044 0.000 0.012 0.000 0.944
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.6459 0.12559 0.104 0.528 0.028 0.340 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 5 0.5022 0.40090 0.332 0.000 0.048 0.000 0.620
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0404 0.73970 0.000 0.988 0.012 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1197 0.67717 0.952 0.048 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 5 0.4161 0.30619 0.392 0.000 0.000 0.000 0.608
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.7582 0.18798 0.300 0.040 0.352 0.000 0.308
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.4626 0.55554 0.020 0.000 0.616 0.000 0.364
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.6478 0.50592 0.044 0.516 0.364 0.000 0.076
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.4728 0.55968 0.700 0.000 0.060 0.000 0.240
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5518 0.24489 0.544 0.000 0.384 0.000 0.072
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1331 0.68487 0.952 0.000 0.040 0.008 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5748 0.22084 0.020 0.444 0.044 0.492 0.000
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#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.4375 0.64370 0.136 0.784 0.016 0.000 0.064
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.3238 0.68237 0.136 0.836 0.028 0.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0794 0.73540 0.000 0.972 0.000 0.028 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.5088 0.56966 0.252 0.080 0.000 0.668 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.1608 0.73488 0.000 0.928 0.072 0.000 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.1597 0.68339 0.940 0.000 0.048 0.000 0.012
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.0404 0.84202 0.012 0.000 0.000 0.988 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.3154 0.60694 0.836 0.012 0.004 0.000 0.148
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.2329 0.63950 0.876 0.000 0.000 0.000 0.124
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.6800 -0.11026 0.000 0.364 0.292 0.000 0.344
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.2917 0.72269 0.052 0.884 0.012 0.052 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.6648 0.55499 0.056 0.596 0.212 0.000 0.136
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.1557 0.73885 0.008 0.940 0.052 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0880 0.73932 0.000 0.968 0.032 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 5 0.4037 0.57091 0.176 0.012 0.028 0.000 0.784
#> D85CB054-7F54-4383-96C0-6C99761B84E7 5 0.4256 0.27464 0.436 0.000 0.000 0.000 0.564
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.3452 0.63879 0.852 0.000 0.092 0.032 0.024
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.4276 0.68670 0.032 0.724 0.244 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 5 0.4166 0.38345 0.348 0.000 0.004 0.000 0.648
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.1310 0.68258 0.956 0.000 0.020 0.000 0.024
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.4335 0.59232 0.760 0.000 0.072 0.000 0.168
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.1341 0.67491 0.944 0.000 0.000 0.000 0.056
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0880 0.68198 0.968 0.000 0.000 0.000 0.032
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.4963 0.56020 0.040 0.000 0.608 0.000 0.352
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5944 0.55744 0.020 0.092 0.608 0.000 0.280
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.3339 0.65383 0.840 0.000 0.000 0.048 0.112
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.3932 0.63136 0.828 0.000 0.092 0.036 0.044
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.1043 0.73629 0.000 0.960 0.040 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0510 0.68528 0.984 0.000 0.016 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.6512 0.25728 0.348 0.000 0.452 0.000 0.200
#> D957A2ED-97CD-4107-90A5-73C7691A5681 5 0.2230 0.44146 0.000 0.000 0.116 0.000 0.884
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0510 0.68386 0.984 0.016 0.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.7142 0.00456 0.428 0.400 0.072 0.000 0.100
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.5647 -0.04958 0.476 0.028 0.028 0.000 0.468
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.3949 0.42216 0.668 0.000 0.332 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.2989 0.70617 0.080 0.872 0.004 0.000 0.044
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.3586 0.59262 0.264 0.000 0.000 0.736 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.5956 -0.05876 0.000 0.476 0.416 0.000 0.108
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0807 0.74073 0.012 0.976 0.012 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.6458 0.21721 0.496 0.000 0.280 0.000 0.224
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.3628 0.57304 0.012 0.772 0.216 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 5 0.3086 0.32621 0.004 0.000 0.180 0.000 0.816
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.6917 0.13285 0.012 0.460 0.272 0.000 0.256
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.6062 0.52937 0.672 0.000 0.092 0.160 0.076
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.73947 0.000 1.000 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.2520 0.67353 0.896 0.000 0.048 0.000 0.056
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.6934 0.06933 0.456 0.068 0.392 0.000 0.084
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.4015 0.61897 0.000 0.652 0.348 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.5375 0.55214 0.136 0.664 0.000 0.200 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.1251 0.68356 0.956 0.000 0.036 0.000 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.5272 0.51462 0.052 0.000 0.552 0.000 0.396
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6326 -0.05965 0.460 0.000 0.380 0.000 0.160
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.2813 0.62625 0.832 0.000 0.000 0.168 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.73947 0.000 1.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.1792 0.73260 0.000 0.916 0.084 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4866 0.56287 0.036 0.000 0.620 0.000 0.344
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.5596 0.34233 0.596 0.304 0.100 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 5 0.2351 0.44858 0.016 0.000 0.088 0.000 0.896
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4851 0.56483 0.036 0.000 0.624 0.000 0.340
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 5 0.3109 0.57885 0.200 0.000 0.000 0.000 0.800
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.3977 0.25390 0.032 0.000 0.204 0.000 0.764
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4929 0.57139 0.004 0.032 0.624 0.000 0.340
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.6494 0.20651 0.380 0.004 0.452 0.000 0.164
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 5 0.4075 0.56335 0.160 0.000 0.060 0.000 0.780
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3336 0.56218 0.772 0.000 0.000 0.000 0.228
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.5978 0.32866 0.024 0.624 0.012 0.280 0.060
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.3552 0.71261 0.052 0.860 0.044 0.040 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 5 0.2929 0.56484 0.180 0.000 0.000 0.000 0.820
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.6725 -0.01004 0.000 0.400 0.256 0.000 0.344
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.6692 0.05553 0.416 0.000 0.336 0.000 0.248
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 4 0.7504 0.52276 0.028 0.108 0.272 0.528 0.064
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0798 0.73874 0.008 0.976 0.016 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1205 0.68403 0.956 0.000 0.040 0.004 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 5 0.3612 0.56099 0.268 0.000 0.000 0.000 0.732
#> 5E03E52F-957D-455B-A007-19714FAA818A 5 0.3957 0.21643 0.008 0.000 0.280 0.000 0.712
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.1121 0.67711 0.956 0.000 0.000 0.000 0.044
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.6451 0.26011 0.364 0.000 0.452 0.000 0.184
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.7808 0.33062 0.084 0.552 0.076 0.212 0.076
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1205 0.68403 0.956 0.000 0.040 0.004 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.6076 0.67683 0.032 0.168 0.044 0.692 0.064
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0609 0.68549 0.980 0.000 0.000 0.020 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4135 0.41045 0.656 0.000 0.340 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 5 0.5013 0.29501 0.100 0.000 0.204 0.000 0.696
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6754 0.08891 0.396 0.000 0.332 0.000 0.272
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.3476 0.47868 0.076 0.000 0.088 0.000 0.836
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3999 0.49182 0.000 0.344 0.000 0.656 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 4 0.8287 0.03317 0.164 0.348 0.028 0.380 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0794 0.73769 0.000 0.972 0.028 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.1074 0.68442 0.968 0.004 0.000 0.012 0.016
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.5099 0.34639 0.612 0.000 0.336 0.000 0.052
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2377 0.63557 0.872 0.000 0.000 0.000 0.128
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4794 0.57117 0.000 0.032 0.624 0.000 0.344
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.5510 0.24997 0.380 0.548 0.000 0.000 0.072
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2625 0.69936 0.108 0.876 0.016 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.1121 0.68334 0.956 0.000 0.000 0.044 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.6229 0.63584 0.172 0.056 0.028 0.680 0.064
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 5 0.3203 0.40102 0.012 0.000 0.168 0.000 0.820
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 5 0.3684 0.54945 0.280 0.000 0.000 0.000 0.720
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.4360 0.55238 0.184 0.000 0.064 0.000 0.752
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 5 0.3558 0.51255 0.064 0.000 0.108 0.000 0.828
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1493 0.73503 0.000 0.948 0.028 0.024 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 5 0.4300 0.15520 0.476 0.000 0.000 0.000 0.524
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.4637 0.21653 0.452 0.000 0.012 0.000 0.536
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0880 0.68175 0.968 0.000 0.000 0.000 0.032
#> E6446572-BFA9-4018-89B3-7E4519EBE072 5 0.4644 0.20967 0.460 0.000 0.012 0.000 0.528
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.84781 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.5293 -0.14546 0.492 0.000 0.048 0.000 0.460
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2645 0.72734 0.044 0.888 0.068 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.4794 0.57117 0.000 0.032 0.624 0.000 0.344
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1121 0.73930 0.000 0.956 0.044 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 5 0.4383 0.27978 0.424 0.000 0.004 0.000 0.572
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5283 0.26166 0.572 0.384 0.032 0.000 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.6036 0.16125 0.432 0.000 0.452 0.000 0.116
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2230 0.64812 0.884 0.000 0.000 0.000 0.116
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.3208 0.64200 0.084 0.044 0.000 0.000 0.848 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2294 0.70699 0.036 0.072 0.892 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.3221 0.53671 0.000 0.000 0.000 0.736 0.000 0.264
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4752 0.55868 0.000 0.676 0.000 0.140 0.184 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.3371 0.54513 0.708 0.000 0.292 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4260 0.67853 0.004 0.744 0.136 0.000 0.000 0.116
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3351 0.62821 0.712 0.000 0.000 0.000 0.000 0.288
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.5599 0.59877 0.168 0.096 0.656 0.000 0.000 0.080
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.3584 0.48552 0.688 0.000 0.308 0.000 0.004 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3062 0.84600 0.000 0.144 0.000 0.000 0.824 0.032
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3376 0.67619 0.764 0.000 0.016 0.000 0.000 0.220
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3219 0.62275 0.000 0.792 0.004 0.012 0.192 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4959 0.53429 0.692 0.028 0.000 0.000 0.092 0.188
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1007 0.83621 0.000 0.000 0.000 0.956 0.000 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.3532 0.66696 0.796 0.000 0.140 0.000 0.000 0.064
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.6262 0.39845 0.000 0.120 0.000 0.312 0.512 0.056
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.3876 0.62859 0.000 0.120 0.000 0.772 0.108 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.2597 0.86865 0.000 0.176 0.000 0.000 0.824 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.6092 0.03135 0.016 0.000 0.440 0.380 0.164 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2664 0.63256 0.000 0.816 0.000 0.000 0.184 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.4111 0.52989 0.084 0.000 0.000 0.000 0.176 0.740
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.4845 0.57542 0.000 0.328 0.004 0.000 0.604 0.064
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.3482 0.45930 0.000 0.000 0.000 0.316 0.000 0.684
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.2597 0.86865 0.000 0.176 0.000 0.000 0.824 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.4493 0.47160 0.596 0.000 0.364 0.000 0.000 0.040
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#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.5729 0.30742 0.004 0.252 0.000 0.540 0.204 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.0632 0.64067 0.000 0.000 0.000 0.024 0.000 0.976
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.1908 0.62681 0.004 0.000 0.096 0.000 0.000 0.900
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5029 -0.01460 0.524 0.000 0.400 0.000 0.000 0.076
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 6 0.6782 0.13036 0.320 0.000 0.068 0.000 0.176 0.436
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.3073 0.64163 0.840 0.000 0.080 0.000 0.000 0.080
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.3789 0.38893 0.000 0.584 0.000 0.416 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 4 0.7989 0.14804 0.136 0.168 0.004 0.392 0.036 0.264
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.1714 0.70962 0.000 0.908 0.092 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.2996 0.60017 0.144 0.016 0.000 0.008 0.000 0.832
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.2320 0.61976 0.004 0.000 0.132 0.000 0.000 0.864
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.3620 0.22129 0.352 0.000 0.000 0.000 0.000 0.648
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0865 0.71145 0.036 0.000 0.964 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 6 0.4625 0.15072 0.032 0.424 0.004 0.000 0.000 0.540
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3492 0.70320 0.000 0.788 0.004 0.000 0.032 0.176
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0632 0.64067 0.000 0.000 0.000 0.024 0.000 0.976
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.6023 0.43522 0.000 0.108 0.000 0.608 0.192 0.092
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.3351 0.55038 0.712 0.000 0.288 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3514 0.67386 0.752 0.000 0.020 0.000 0.000 0.228
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1908 0.65578 0.916 0.000 0.028 0.000 0.000 0.056
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.3244 0.56892 0.732 0.000 0.268 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3219 0.62275 0.000 0.792 0.004 0.012 0.192 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3684 0.53352 0.628 0.000 0.000 0.000 0.000 0.372
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3670 0.60762 0.736 0.000 0.024 0.000 0.000 0.240
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.2527 0.59705 0.168 0.000 0.000 0.000 0.000 0.832
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3838 0.37283 0.552 0.000 0.000 0.000 0.000 0.448
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.86974 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 6 0.3961 -0.08717 0.440 0.000 0.004 0.000 0.000 0.556
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5360 0.66388 0.012 0.680 0.088 0.000 0.036 0.184
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0937 0.71170 0.040 0.000 0.960 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.3979 -0.04608 0.000 0.540 0.004 0.000 0.456 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3446 0.60684 0.692 0.000 0.000 0.000 0.000 0.308
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.4802 0.49283 0.020 0.584 0.028 0.000 0.000 0.368
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.5633 0.08124 0.148 0.000 0.412 0.000 0.000 0.440
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.1663 0.61709 0.088 0.000 0.000 0.000 0.000 0.912
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.961 0.977 0.4779 0.518 0.518
#> 3 3 0.564 0.710 0.837 0.2020 0.965 0.933
#> 4 4 0.543 0.592 0.767 0.1596 0.788 0.581
#> 5 5 0.559 0.599 0.742 0.1161 0.840 0.559
#> 6 6 0.593 0.559 0.703 0.0569 0.941 0.790
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.1184 0.9714 0.016 0.984
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.1414 0.9699 0.020 0.980
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.0938 0.9829 0.988 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.1184 0.9685 0.016 0.984
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1184 0.9714 0.016 0.984
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.1184 0.9851 0.984 0.016
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9988 0.0799 0.480 0.520
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0376 0.9875 0.996 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0000 0.9878 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.1184 0.9840 0.984 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.1184 0.9714 0.016 0.984
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0672 0.9868 0.992 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1184 0.9714 0.016 0.984
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0376 0.9875 0.996 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.2043 0.9522 0.032 0.968
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0376 0.9875 0.996 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.1414 0.9699 0.020 0.980
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0376 0.9655 0.004 0.996
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1184 0.9714 0.016 0.984
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.1184 0.9714 0.016 0.984
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0672 0.9642 0.008 0.992
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0938 0.9702 0.012 0.988
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9878 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1184 0.9714 0.016 0.984
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9878 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.1184 0.9714 0.016 0.984
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.1184 0.9851 0.984 0.016
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0376 0.9875 0.996 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0672 0.9868 0.992 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0672 0.9868 0.992 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0938 0.9829 0.988 0.012
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1184 0.9714 0.016 0.984
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0672 0.9642 0.008 0.992
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9878 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0376 0.9875 0.996 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.1184 0.9714 0.016 0.984
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.7883 0.7179 0.236 0.764
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0938 0.9829 0.988 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9878 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.0672 0.9642 0.008 0.992
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0376 0.9875 0.996 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0672 0.9868 0.992 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0938 0.9702 0.012 0.988
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0376 0.9875 0.996 0.004
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.1184 0.9691 0.016 0.984
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0938 0.9829 0.988 0.012
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0672 0.9642 0.008 0.992
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.9878 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0672 0.9868 0.992 0.008
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1184 0.9714 0.016 0.984
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9878 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0938 0.9846 0.988 0.012
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.1184 0.9714 0.016 0.984
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0672 0.9868 0.992 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9878 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2043 0.9676 0.968 0.032
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0938 0.9702 0.012 0.988
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1184 0.9714 0.016 0.984
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0376 0.9875 0.996 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.1184 0.9714 0.016 0.984
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0672 0.9868 0.992 0.008
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1184 0.9714 0.016 0.984
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9878 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0672 0.9868 0.992 0.008
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0938 0.9829 0.988 0.012
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0938 0.9829 0.988 0.012
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.1184 0.9714 0.016 0.984
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0672 0.9868 0.992 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0938 0.9846 0.988 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.9878 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1184 0.9714 0.016 0.984
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.7376 0.7356 0.792 0.208
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1184 0.9714 0.016 0.984
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.1184 0.9714 0.016 0.984
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.0672 0.9868 0.992 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.0672 0.9642 0.008 0.992
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0938 0.9829 0.988 0.012
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.8443 0.6652 0.272 0.728
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.0938 0.9829 0.988 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.0938 0.9829 0.988 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0672 0.9868 0.992 0.008
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.1184 0.9714 0.016 0.984
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0672 0.9868 0.992 0.008
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.0376 0.9875 0.996 0.004
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0672 0.9861 0.992 0.008
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0938 0.9702 0.012 0.988
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9878 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.0938 0.9829 0.988 0.012
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#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.1414 0.9699 0.020 0.980
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9878 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0938 0.9702 0.012 0.988
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9878 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9878 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.9878 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 2 0.0672 0.9642 0.008 0.992
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0376 0.9875 0.996 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0376 0.9875 0.996 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.1184 0.9714 0.016 0.984
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.1184 0.9714 0.016 0.984
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.3733 0.9215 0.072 0.928
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.9878 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.0672 0.9642 0.008 0.992
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0938 0.9829 0.988 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0376 0.9875 0.996 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0938 0.9846 0.988 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0672 0.9868 0.992 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1184 0.9714 0.016 0.984
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9878 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.1184 0.9714 0.016 0.984
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0938 0.9829 0.988 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0672 0.9868 0.992 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0376 0.9875 0.996 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.1184 0.9851 0.984 0.016
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1184 0.9714 0.016 0.984
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0376 0.9875 0.996 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0672 0.9850 0.992 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9878 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0672 0.9868 0.992 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.1414 0.9699 0.020 0.980
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0376 0.9872 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.1184 0.9685 0.016 0.984
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.1184 0.9817 0.984 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1184 0.9714 0.016 0.984
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0672 0.9868 0.992 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0376 0.9875 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0938 0.9829 0.988 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0672 0.9868 0.992 0.008
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3941 0.56206 0.156 0.844 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.6252 -0.66356 0.444 0.556 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.5706 0.76664 0.320 0.000 0.680
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.6252 -0.71133 0.444 0.556 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1289 0.72676 0.032 0.968 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4235 0.83435 0.176 0.000 0.824
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9658 -0.13911 0.212 0.420 0.368
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0237 0.87372 0.004 0.000 0.996
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.4504 0.84095 0.196 0.000 0.804
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4842 0.81619 0.224 0.000 0.776
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2959 0.65224 0.100 0.900 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0237 0.87372 0.004 0.000 0.996
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0424 0.74119 0.008 0.992 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.3550 0.86176 0.080 0.024 0.896
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.9813 -0.28284 0.304 0.428 0.268
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0892 0.87453 0.020 0.000 0.980
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.6252 -0.66356 0.444 0.556 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.3551 0.56555 0.132 0.868 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1753 0.71238 0.048 0.952 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0237 0.74147 0.004 0.996 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.3752 0.54292 0.144 0.856 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0237 0.74147 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 3 0.2796 0.86468 0.092 0.000 0.908
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0237 0.74147 0.004 0.996 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.6295 0.73382 0.236 0.036 0.728
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0237 0.74147 0.004 0.996 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4654 0.84382 0.208 0.000 0.792
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.4848 0.83071 0.128 0.036 0.836
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.0424 0.87380 0.008 0.000 0.992
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.0237 0.87372 0.004 0.000 0.996
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4702 0.81868 0.212 0.000 0.788
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0237 0.74147 0.004 0.996 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.6244 0.97866 0.560 0.440 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.0892 0.87479 0.020 0.000 0.980
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.1031 0.87496 0.024 0.000 0.976
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.3879 0.52891 0.152 0.848 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.9059 -0.10011 0.136 0.456 0.408
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.4452 0.84811 0.192 0.000 0.808
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.4504 0.80770 0.196 0.000 0.804
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.6235 0.98260 0.564 0.436 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.0237 0.87372 0.004 0.000 0.996
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.2537 0.86516 0.080 0.000 0.920
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0424 0.74075 0.008 0.992 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 3 0.4452 0.81309 0.192 0.000 0.808
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.7980 -0.01756 0.172 0.660 0.168
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.5397 0.76785 0.280 0.000 0.720
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.3619 0.55696 0.136 0.864 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.2537 0.86445 0.080 0.000 0.920
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.2261 0.86785 0.068 0.000 0.932
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1529 0.71827 0.040 0.960 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.1031 0.87575 0.024 0.000 0.976
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.1289 0.87596 0.032 0.000 0.968
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0237 0.74012 0.004 0.996 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.0892 0.87606 0.020 0.000 0.980
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.2711 0.85384 0.088 0.000 0.912
#> 311D089C-33F1-4722-9118-F56427C5C128 3 0.5764 0.80754 0.124 0.076 0.800
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0237 0.74147 0.004 0.996 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1753 0.71288 0.048 0.952 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.2796 0.86569 0.092 0.000 0.908
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0892 0.73779 0.020 0.980 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.0592 0.87368 0.012 0.000 0.988
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0424 0.73856 0.008 0.992 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.3551 0.84743 0.132 0.000 0.868
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.2165 0.86939 0.064 0.000 0.936
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.4605 0.84712 0.204 0.000 0.796
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.5431 0.76781 0.284 0.000 0.716
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3482 0.61026 0.128 0.872 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.4750 0.80034 0.216 0.000 0.784
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.2356 0.86992 0.072 0.000 0.928
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.2448 0.86679 0.076 0.000 0.924
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0592 0.73691 0.012 0.988 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.9528 0.24858 0.228 0.288 0.484
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0424 0.73856 0.008 0.992 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0424 0.74133 0.008 0.992 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.4692 0.85779 0.168 0.012 0.820
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.6235 0.98260 0.564 0.436 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.5327 0.77394 0.272 0.000 0.728
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.7419 0.11431 0.088 0.680 0.232
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.5254 0.77955 0.264 0.000 0.736
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.5810 0.77117 0.336 0.000 0.664
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.3412 0.85129 0.124 0.000 0.876
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0237 0.74147 0.004 0.996 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 3 0.3116 0.85730 0.108 0.000 0.892
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.5325 0.83028 0.248 0.004 0.748
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.6264 0.72942 0.244 0.032 0.724
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0424 0.74075 0.008 0.992 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.4062 0.82672 0.164 0.000 0.836
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.5397 0.76785 0.280 0.000 0.720
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0424 0.87456 0.008 0.000 0.992
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0983 0.73671 0.016 0.980 0.004
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.0424 0.87440 0.008 0.000 0.992
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.2448 0.86841 0.076 0.000 0.924
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 3 0.2878 0.86068 0.096 0.000 0.904
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0237 0.74147 0.004 0.996 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.0237 0.87372 0.004 0.000 0.996
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.3482 0.61026 0.128 0.872 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0592 0.73691 0.012 0.988 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0237 0.74147 0.004 0.996 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.6235 0.98260 0.564 0.436 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0237 0.74147 0.004 0.996 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.1163 0.87713 0.028 0.000 0.972
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.0000 0.87404 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 3 0.4914 0.83692 0.088 0.068 0.844
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0424 0.73856 0.008 0.992 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.2878 0.86294 0.096 0.000 0.904
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5754 0.79893 0.296 0.004 0.700
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.9367 0.43798 0.292 0.204 0.504
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0892 0.87453 0.020 0.000 0.980
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0237 0.74147 0.004 0.996 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 3 0.6633 0.73657 0.212 0.060 0.728
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6463 0.27593 0.080 0.756 0.164
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.1163 0.73237 0.028 0.972 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0424 0.74096 0.008 0.992 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.1163 0.87412 0.028 0.000 0.972
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.1643 0.71509 0.044 0.956 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0237 0.74147 0.004 0.996 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.1031 0.87537 0.024 0.000 0.976
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0592 0.73691 0.012 0.988 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.5138 0.79285 0.252 0.000 0.748
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 3 0.4654 0.80549 0.208 0.000 0.792
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.2959 0.86389 0.100 0.000 0.900
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 3 0.3482 0.84416 0.128 0.000 0.872
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0892 0.73690 0.020 0.980 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.5733 0.75843 0.324 0.000 0.676
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.1529 0.71881 0.040 0.960 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 2 0.6509 -0.76154 0.472 0.524 0.004
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.8292 0.00149 0.124 0.612 0.264
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.2261 0.86702 0.068 0.000 0.932
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 3 0.1163 0.87343 0.028 0.000 0.972
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.5948 -0.37786 0.360 0.640 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.0592 0.87400 0.012 0.000 0.988
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0237 0.74147 0.004 0.996 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.3752 0.85610 0.144 0.000 0.856
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#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.1529 0.71754 0.040 0.960 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.5254 0.78015 0.264 0.000 0.736
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.0237 0.87372 0.004 0.000 0.996
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.1643 0.87640 0.044 0.000 0.956
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.2537 0.86989 0.080 0.000 0.920
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0592 0.73691 0.012 0.988 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.0424 0.87403 0.008 0.000 0.992
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.1643 0.87540 0.044 0.000 0.956
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.1031 0.87514 0.024 0.000 0.976
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.0592 0.87427 0.012 0.000 0.988
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.6252 -0.66356 0.444 0.556 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0424 0.87416 0.008 0.000 0.992
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0592 0.73691 0.012 0.988 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.6667 0.72885 0.368 0.016 0.616
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0424 0.73856 0.008 0.992 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.0747 0.87363 0.016 0.000 0.984
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.5696 0.80488 0.136 0.064 0.800
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4121 0.84055 0.168 0.000 0.832
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.2537 0.86536 0.080 0.000 0.920
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5338 0.69105 0.140 0.768 0.016 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4804 0.75089 0.016 0.276 0.000 0.708
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2216 0.61337 0.092 0.000 0.908 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4364 0.79994 0.016 0.220 0.000 0.764
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1452 0.87014 0.008 0.956 0.000 0.036
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4836 0.35982 0.320 0.000 0.672 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.9177 -0.06676 0.240 0.340 0.344 0.076
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.5085 0.59119 0.616 0.000 0.376 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3569 0.56770 0.196 0.000 0.804 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2647 0.60421 0.120 0.000 0.880 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2662 0.84278 0.000 0.900 0.016 0.084
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5150 0.56423 0.596 0.000 0.396 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1118 0.87152 0.000 0.964 0.000 0.036
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5228 0.54171 0.664 0.000 0.312 0.024
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.8023 0.49814 0.284 0.272 0.008 0.436
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5290 -0.25086 0.476 0.000 0.516 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.5426 0.79765 0.060 0.232 0.000 0.708
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4053 0.68121 0.000 0.768 0.004 0.228
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2665 0.84616 0.008 0.900 0.004 0.088
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.1109 0.87237 0.000 0.968 0.004 0.028
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.4303 0.69236 0.008 0.768 0.004 0.220
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0592 0.87502 0.000 0.984 0.000 0.016
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.4019 0.64283 0.792 0.000 0.196 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0592 0.87369 0.000 0.984 0.000 0.016
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.4352 0.56122 0.816 0.000 0.080 0.104
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0592 0.87369 0.000 0.984 0.000 0.016
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4564 0.40915 0.328 0.000 0.672 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4685 0.60355 0.784 0.000 0.156 0.060
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.5085 0.59135 0.616 0.000 0.376 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.5150 0.56350 0.596 0.000 0.396 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2281 0.63020 0.096 0.000 0.904 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1109 0.87237 0.000 0.968 0.004 0.028
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.5112 0.51501 0.560 0.000 0.436 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.5229 -0.02991 0.428 0.000 0.564 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.6529 0.29393 0.088 0.600 0.004 0.308
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.6702 0.12840 0.572 0.344 0.012 0.072
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.4907 0.17614 0.420 0.000 0.580 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.5032 0.61679 0.764 0.000 0.156 0.080
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.2871 0.87946 0.032 0.072 0.000 0.896
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.5085 0.58964 0.616 0.000 0.376 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4857 0.63168 0.668 0.000 0.324 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0336 0.87277 0.000 0.992 0.000 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.2773 0.49674 0.900 0.000 0.028 0.072
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.7583 0.03643 0.216 0.508 0.004 0.272
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1022 0.63264 0.032 0.000 0.968 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.4374 0.67847 0.008 0.760 0.004 0.228
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3978 0.62897 0.796 0.000 0.192 0.012
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4454 0.58160 0.692 0.000 0.308 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1489 0.86986 0.000 0.952 0.004 0.044
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5016 0.56887 0.600 0.000 0.396 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.5281 0.43979 0.528 0.000 0.464 0.008
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0817 0.87392 0.000 0.976 0.000 0.024
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5147 -0.18506 0.460 0.000 0.536 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.5416 0.63426 0.692 0.000 0.260 0.048
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.4941 0.58178 0.796 0.016 0.120 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0336 0.87277 0.000 0.992 0.000 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1888 0.85920 0.016 0.940 0.000 0.044
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.5004 0.13291 0.392 0.000 0.604 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.1890 0.86193 0.008 0.936 0.000 0.056
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.5070 0.59605 0.620 0.000 0.372 0.008
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0895 0.87371 0.004 0.976 0.000 0.020
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.4374 0.59834 0.812 0.000 0.120 0.068
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4608 0.64348 0.692 0.000 0.304 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.4989 0.12638 0.472 0.000 0.528 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1389 0.63596 0.048 0.000 0.952 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3722 0.80755 0.044 0.868 0.016 0.072
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3081 0.49255 0.888 0.000 0.048 0.064
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.5236 -0.03126 0.432 0.000 0.560 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.4908 0.63779 0.692 0.000 0.292 0.016
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1022 0.87261 0.000 0.968 0.000 0.032
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.6984 -0.16256 0.520 0.392 0.020 0.068
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0927 0.87343 0.008 0.976 0.000 0.016
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0817 0.87376 0.000 0.976 0.000 0.024
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.4817 0.20689 0.388 0.000 0.612 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1637 0.63394 0.060 0.000 0.940 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.6431 0.43128 0.284 0.640 0.040 0.036
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.2081 0.63457 0.084 0.000 0.916 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.2888 0.61188 0.124 0.000 0.872 0.004
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.4621 0.63847 0.708 0.000 0.284 0.008
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0927 0.87369 0.008 0.976 0.000 0.016
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.4663 0.60774 0.788 0.000 0.148 0.064
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.4643 0.39937 0.344 0.000 0.656 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.4321 0.51385 0.812 0.004 0.040 0.144
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0804 0.87193 0.008 0.980 0.000 0.012
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.5050 0.62233 0.756 0.000 0.176 0.068
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0817 0.62943 0.024 0.000 0.976 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.5159 0.60004 0.624 0.000 0.364 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1297 0.86862 0.020 0.964 0.000 0.016
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.5150 0.56980 0.596 0.000 0.396 0.008
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.5263 -0.14678 0.448 0.000 0.544 0.008
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.4716 0.62883 0.764 0.000 0.196 0.040
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0592 0.87369 0.000 0.984 0.000 0.016
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.5112 0.58951 0.608 0.000 0.384 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.3659 0.81834 0.032 0.868 0.016 0.084
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1545 0.86945 0.008 0.952 0.000 0.040
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.1610 0.86871 0.000 0.952 0.016 0.032
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0592 0.87369 0.000 0.984 0.000 0.016
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.5024 0.60344 0.632 0.000 0.360 0.008
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.5110 0.61057 0.636 0.000 0.352 0.012
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.5568 0.49634 0.664 0.008 0.300 0.028
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.1004 0.87419 0.004 0.972 0.000 0.024
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.5060 0.08275 0.412 0.000 0.584 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.4049 0.51551 0.212 0.000 0.780 0.008
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.7392 0.38877 0.188 0.020 0.592 0.200
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.5294 -0.28794 0.484 0.000 0.508 0.008
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0707 0.87379 0.000 0.980 0.000 0.020
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.2088 0.47316 0.928 0.004 0.004 0.064
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.5840 0.48547 0.264 0.672 0.004 0.060
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.1985 0.85968 0.016 0.940 0.004 0.040
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0592 0.87223 0.000 0.984 0.000 0.016
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.4761 0.60019 0.664 0.000 0.332 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.2342 0.84506 0.008 0.912 0.000 0.080
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0592 0.87369 0.000 0.984 0.000 0.016
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.5163 0.10589 0.516 0.000 0.480 0.004
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0707 0.87361 0.000 0.980 0.000 0.020
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.1211 0.63277 0.040 0.000 0.960 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.3164 0.49581 0.884 0.000 0.052 0.064
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.5060 0.07271 0.412 0.000 0.584 0.004
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.5386 0.63649 0.708 0.000 0.236 0.056
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0927 0.87259 0.008 0.976 0.000 0.016
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.6315 -0.22249 0.508 0.000 0.432 0.060
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.2328 0.85150 0.004 0.924 0.016 0.056
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.5032 0.85394 0.072 0.152 0.004 0.772
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.6902 0.05239 0.452 0.460 0.008 0.080
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.4830 0.53243 0.608 0.000 0.392 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.4857 0.62793 0.668 0.000 0.324 0.008
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.5443 0.08218 0.008 0.532 0.004 0.456
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.5172 0.55035 0.588 0.000 0.404 0.008
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0817 0.87374 0.000 0.976 0.000 0.024
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.4730 0.27919 0.364 0.000 0.636 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.5294 0.34674 0.508 0.000 0.484 0.008
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.4978 0.62614 0.664 0.000 0.324 0.012
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.2216 0.61160 0.092 0.000 0.908 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.1816 0.86931 0.024 0.948 0.004 0.024
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.4513 0.60183 0.804 0.000 0.120 0.076
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.1109 0.87237 0.000 0.968 0.004 0.028
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0817 0.62943 0.024 0.000 0.976 0.000
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#> 1122039D-5785-4F70-9916-17C585453512 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4939 0.55396 0.740 0.000 0.220 0.040
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.5097 0.00259 0.428 0.000 0.568 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.3625 0.76625 0.012 0.828 0.000 0.160
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.1042 0.87295 0.008 0.972 0.000 0.020
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5067 0.69215 0.104 0.796 0.076 0.024
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4328 0.63151 0.748 0.000 0.244 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.2928 0.88246 0.052 0.052 0.000 0.896
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.4936 0.23273 0.372 0.000 0.624 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.5070 0.59397 0.620 0.000 0.372 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1867 0.63544 0.072 0.000 0.928 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4769 0.61391 0.684 0.000 0.308 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0707 0.87361 0.000 0.980 0.000 0.020
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.4879 0.59912 0.780 0.000 0.128 0.092
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0921 0.87312 0.000 0.972 0.000 0.028
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3208 0.59917 0.148 0.000 0.848 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.5112 0.58043 0.608 0.000 0.384 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4800 0.42897 0.656 0.000 0.340 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4991 0.16528 0.388 0.000 0.608 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1211 0.87013 0.000 0.960 0.000 0.040
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.5244 0.58912 0.600 0.000 0.388 0.012
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5167 0.35249 0.508 0.000 0.488 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.5138 0.57259 0.600 0.000 0.392 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4955 0.61655 0.648 0.000 0.344 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4804 0.75089 0.016 0.276 0.000 0.708
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.5038 0.62272 0.652 0.000 0.336 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.1356 0.87231 0.008 0.960 0.000 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2675 0.59905 0.100 0.000 0.892 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0707 0.87361 0.000 0.980 0.000 0.020
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4917 0.61912 0.656 0.000 0.336 0.008
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4475 0.63849 0.748 0.004 0.240 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4406 0.42756 0.300 0.000 0.700 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4262 0.65061 0.756 0.000 0.236 0.008
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4631 0.73163 0.000 0.728 0.224 0.024 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.2806 0.83338 0.000 0.152 0.000 0.844 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4840 0.79360 0.320 0.000 0.640 0.000 0.040
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.2358 0.85686 0.000 0.104 0.000 0.888 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2962 0.84621 0.000 0.868 0.084 0.048 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.3242 0.39524 0.816 0.000 0.172 0.000 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 5 0.8448 0.04185 0.076 0.328 0.240 0.024 0.332
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2583 0.63664 0.864 0.000 0.004 0.000 0.132
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.5645 0.74128 0.376 0.000 0.540 0.000 0.084
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.5234 0.64041 0.460 0.000 0.496 0.000 0.044
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2727 0.83964 0.000 0.868 0.116 0.016 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2124 0.64470 0.900 0.000 0.004 0.000 0.096
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2362 0.84910 0.000 0.900 0.076 0.024 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5583 0.31303 0.572 0.000 0.072 0.004 0.352
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.6248 0.20190 0.000 0.084 0.020 0.456 0.440
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0609 0.58195 0.980 0.000 0.020 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.2806 0.83338 0.000 0.152 0.000 0.844 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4712 0.72849 0.000 0.736 0.080 0.180 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.3848 0.82016 0.000 0.816 0.076 0.104 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2069 0.84904 0.000 0.912 0.076 0.012 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.3895 0.72275 0.000 0.796 0.032 0.164 0.008
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2233 0.84890 0.000 0.904 0.080 0.016 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.3409 0.67655 0.160 0.000 0.024 0.000 0.816
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.85284 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 5 0.4041 0.70652 0.064 0.000 0.020 0.100 0.816
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0162 0.85282 0.000 0.996 0.000 0.000 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.5240 0.19218 0.656 0.000 0.252 0.000 0.092
#> EE97212E-8D5D-4548-8DD2-317049601FDB 5 0.3755 0.68889 0.140 0.000 0.032 0.012 0.816
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3427 0.61261 0.796 0.000 0.012 0.000 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2488 0.64578 0.872 0.000 0.004 0.000 0.124
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4713 0.71034 0.440 0.000 0.544 0.000 0.016
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2069 0.84904 0.000 0.912 0.076 0.012 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0671 0.90284 0.000 0.016 0.000 0.980 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2824 0.64825 0.864 0.000 0.020 0.000 0.116
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1753 0.58220 0.936 0.000 0.032 0.000 0.032
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.5693 0.41836 0.000 0.572 0.028 0.360 0.040
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 5 0.6169 0.36923 0.016 0.236 0.036 0.068 0.644
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6778 -0.05095 0.380 0.000 0.340 0.000 0.280
#> A84EA172-9823-40E9-BC22-C882725DD1C8 5 0.4288 0.71146 0.088 0.000 0.020 0.092 0.800
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0671 0.90284 0.000 0.016 0.000 0.980 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.2843 0.63142 0.848 0.000 0.008 0.000 0.144
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4953 0.20491 0.532 0.000 0.028 0.000 0.440
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1372 0.85123 0.000 0.956 0.024 0.016 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.4781 0.63568 0.112 0.000 0.160 0.000 0.728
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.7607 -0.02865 0.000 0.392 0.048 0.300 0.260
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4278 0.72064 0.452 0.000 0.548 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.3693 0.72839 0.000 0.808 0.032 0.156 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E 5 0.3994 0.64709 0.188 0.000 0.040 0.000 0.772
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4010 0.58030 0.760 0.000 0.032 0.000 0.208
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2597 0.84884 0.000 0.884 0.092 0.024 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5454 0.29984 0.532 0.000 0.064 0.000 0.404
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3184 0.61897 0.852 0.000 0.048 0.000 0.100
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2362 0.84994 0.000 0.900 0.076 0.024 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.1956 0.53704 0.916 0.000 0.076 0.000 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 5 0.5415 0.04323 0.464 0.000 0.016 0.028 0.492
#> 311D089C-33F1-4722-9118-F56427C5C128 5 0.3731 0.70714 0.096 0.004 0.020 0.040 0.840
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2206 0.85678 0.000 0.912 0.068 0.016 0.004
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3689 0.83116 0.000 0.828 0.076 0.092 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.2179 0.50792 0.896 0.000 0.100 0.000 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.3180 0.83973 0.000 0.856 0.076 0.068 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3171 0.61512 0.816 0.000 0.008 0.000 0.176
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0404 0.85227 0.000 0.988 0.000 0.012 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 5 0.3320 0.70555 0.124 0.000 0.016 0.016 0.844
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4016 0.51622 0.716 0.000 0.012 0.000 0.272
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6510 0.25217 0.488 0.000 0.260 0.000 0.252
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.4546 0.70517 0.460 0.000 0.532 0.000 0.008
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3416 0.82820 0.000 0.840 0.124 0.020 0.016
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 5 0.6190 0.47972 0.236 0.000 0.172 0.008 0.584
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5233 0.48149 0.684 0.000 0.168 0.000 0.148
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 5 0.4990 0.62899 0.232 0.000 0.012 0.056 0.700
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.2362 0.84994 0.000 0.900 0.076 0.024 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.8055 0.17079 0.040 0.392 0.228 0.028 0.312
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0404 0.85308 0.000 0.988 0.000 0.012 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0324 0.85285 0.000 0.992 0.000 0.004 0.004
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.4036 0.46143 0.788 0.000 0.144 0.000 0.068
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0671 0.90284 0.000 0.016 0.000 0.980 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.4307 -0.64541 0.500 0.000 0.500 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.5858 0.63817 0.044 0.696 0.040 0.032 0.188
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.4538 0.71157 0.452 0.000 0.540 0.000 0.008
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.5452 0.75934 0.292 0.000 0.616 0.000 0.092
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 5 0.4770 0.47878 0.320 0.000 0.036 0.000 0.644
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0162 0.85282 0.000 0.996 0.000 0.000 0.004
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 5 0.4275 0.65848 0.228 0.000 0.008 0.024 0.740
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.6557 0.53771 0.340 0.000 0.448 0.000 0.212
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 5 0.3622 0.70734 0.056 0.000 0.000 0.124 0.820
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1461 0.85076 0.000 0.952 0.028 0.016 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 5 0.4377 0.71181 0.088 0.000 0.024 0.092 0.796
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4264 0.78789 0.376 0.000 0.620 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.4760 0.29711 0.564 0.000 0.020 0.000 0.416
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.2269 0.84871 0.000 0.920 0.028 0.032 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4329 0.49856 0.672 0.000 0.016 0.000 0.312
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.1981 0.55335 0.920 0.000 0.064 0.000 0.016
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 5 0.4466 0.63535 0.232 0.000 0.032 0.008 0.728
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2006 0.85027 0.000 0.916 0.072 0.012 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.2848 0.63204 0.840 0.000 0.004 0.000 0.156
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.3416 0.82820 0.000 0.840 0.124 0.020 0.016
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2446 0.85358 0.000 0.900 0.044 0.056 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.2351 0.84761 0.000 0.896 0.088 0.016 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0671 0.90284 0.000 0.016 0.000 0.980 0.004
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0865 0.85647 0.000 0.972 0.024 0.004 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 5 0.5188 0.15249 0.416 0.000 0.044 0.000 0.540
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.4627 0.22746 0.544 0.000 0.012 0.000 0.444
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.6196 -0.00715 0.468 0.000 0.096 0.012 0.424
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0451 0.85237 0.000 0.988 0.000 0.008 0.004
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.6263 0.38728 0.540 0.000 0.216 0.000 0.244
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5854 0.65196 0.252 0.000 0.596 0.000 0.152
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.7236 0.27066 0.084 0.000 0.472 0.104 0.340
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.1403 0.59621 0.952 0.000 0.024 0.000 0.024
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.2069 0.84904 0.000 0.912 0.076 0.012 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 5 0.4759 0.62542 0.080 0.004 0.168 0.004 0.744
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.5661 0.56580 0.008 0.656 0.020 0.060 0.256
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.2806 0.85385 0.000 0.888 0.052 0.052 0.008
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.3170 0.84804 0.000 0.856 0.104 0.036 0.004
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.3304 0.61907 0.816 0.000 0.016 0.000 0.168
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.3536 0.83111 0.000 0.832 0.084 0.084 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.85284 0.000 1.000 0.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.2074 0.57401 0.920 0.000 0.036 0.000 0.044
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0404 0.85227 0.000 0.988 0.000 0.012 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.4392 0.78685 0.380 0.000 0.612 0.000 0.008
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#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.5295 0.25414 0.540 0.000 0.052 0.000 0.408
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0404 0.85498 0.000 0.988 0.012 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.2325 0.85163 0.000 0.904 0.028 0.068 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4416 0.42781 0.632 0.000 0.012 0.000 0.356
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.5048 0.57162 0.476 0.000 0.492 0.000 0.032
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6175 0.05919 0.508 0.000 0.344 0.000 0.148
#> 887E7408-C7D7-420F-A763-0EE70A316D17 5 0.3464 0.71724 0.096 0.000 0.000 0.068 0.836
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0162 0.85370 0.000 0.996 0.004 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.1270 0.85539 0.000 0.948 0.052 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.2583 0.85024 0.000 0.132 0.000 0.864 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4436 0.77112 0.396 0.000 0.596 0.000 0.008
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 5 0.3276 0.69497 0.132 0.000 0.032 0.000 0.836
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.2067 0.59163 0.920 0.000 0.032 0.000 0.048
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4457 0.79267 0.368 0.000 0.620 0.000 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2873 0.63623 0.856 0.000 0.016 0.000 0.128
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.3152 0.48297 0.840 0.000 0.136 0.000 0.024
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.5434 0.73695 0.232 0.000 0.648 0.000 0.120
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4840 0.24428 0.688 0.000 0.248 0.000 0.064
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.2233 0.64518 0.892 0.000 0.004 0.000 0.104
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.2719 0.63008 0.852 0.000 0.004 0.000 0.144
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.3090 0.84827 0.000 0.860 0.104 0.032 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.8372 0.06924 0.088 0.404 0.196 0.024 0.288
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.1956 0.62686 0.916 0.000 0.008 0.000 0.076
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.5911 -0.40888 0.488 0.000 0.408 0.000 0.104
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4066 0.43960 0.672 0.000 0.004 0.000 0.324
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.2172 0.84874 0.000 0.908 0.076 0.016 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1653 0.85021 0.000 0.944 0.028 0.024 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 5 0.4683 0.70370 0.124 0.000 0.020 0.088 0.768
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1205 0.62368 0.956 0.000 0.004 0.000 0.040
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.4450 -0.58957 0.508 0.000 0.488 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 5 0.5640 0.58533 0.260 0.000 0.020 0.076 0.644
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3409 0.62781 0.816 0.000 0.024 0.000 0.160
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.3482 0.84222 0.000 0.844 0.096 0.052 0.008
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.4104 0.71613 0.008 0.020 0.012 0.788 0.172
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.3197 0.83116 0.000 0.152 0.012 0.832 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 5 0.5322 0.67293 0.180 0.000 0.024 0.088 0.708
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.3375 0.84266 0.000 0.852 0.096 0.040 0.012
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 5 0.4737 0.70338 0.136 0.000 0.024 0.076 0.764
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4201 0.30145 0.592 0.000 0.000 0.000 0.408
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.2674 0.49447 0.868 0.000 0.120 0.000 0.012
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0771 0.90301 0.000 0.020 0.000 0.976 0.004
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4841 0.52741 0.708 0.000 0.084 0.000 0.208
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2193 0.55838 0.912 0.000 0.060 0.000 0.028
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.5119 0.61177 0.000 0.656 0.060 0.280 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.2300 0.85645 0.000 0.908 0.052 0.040 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.6135 0.61558 0.016 0.660 0.096 0.028 0.200
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 5 0.3058 0.69598 0.096 0.000 0.044 0.000 0.860
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0671 0.90284 0.000 0.016 0.000 0.980 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.6436 0.29474 0.504 0.000 0.264 0.000 0.232
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4181 0.54446 0.712 0.000 0.020 0.000 0.268
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.4446 -0.59782 0.520 0.000 0.476 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 5 0.4949 0.51331 0.296 0.000 0.044 0.004 0.656
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2325 0.85599 0.000 0.904 0.068 0.028 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 5 0.4342 0.71187 0.092 0.000 0.020 0.092 0.796
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2813 0.84616 0.000 0.876 0.084 0.040 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4101 -0.08482 0.664 0.000 0.332 0.000 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2612 0.64269 0.868 0.000 0.008 0.000 0.124
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3527 0.61729 0.828 0.000 0.056 0.000 0.116
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.1768 0.53231 0.924 0.000 0.072 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.2813 0.84741 0.000 0.876 0.084 0.040 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4206 0.54346 0.708 0.000 0.020 0.000 0.272
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5766 0.51770 0.616 0.000 0.164 0.000 0.220
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.5415 0.33361 0.552 0.000 0.064 0.000 0.384
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3398 0.58041 0.780 0.000 0.004 0.000 0.216
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.2763 0.83715 0.000 0.148 0.000 0.848 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3966 0.44773 0.664 0.000 0.000 0.000 0.336
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0854 0.85410 0.000 0.976 0.004 0.012 0.008
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.5312 0.75456 0.248 0.000 0.652 0.000 0.100
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0290 0.85229 0.000 0.992 0.000 0.008 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3355 0.60324 0.804 0.000 0.012 0.000 0.184
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 5 0.3722 0.68341 0.144 0.000 0.040 0.004 0.812
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.6300 0.38150 0.420 0.000 0.428 0.000 0.152
#> 2785594A-571A-46B4-A901-CB9C62DC6174 5 0.4341 0.47302 0.364 0.000 0.000 0.008 0.628
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3819 0.67702 0.000 0.652 0.000 0.008 NA 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.2954 0.83104 0.000 0.048 0.000 0.852 NA 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2444 0.71221 0.068 0.000 0.892 0.000 NA 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.3090 0.81071 0.000 0.088 0.000 0.848 NA 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4464 0.71866 0.000 0.676 0.000 0.056 NA 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.4658 0.15332 0.580 0.000 0.376 0.000 NA 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.8389 0.17565 0.032 0.380 0.104 0.036 NA 0.224
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0820 0.63595 0.972 0.000 0.016 0.000 NA 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3460 0.70224 0.084 0.000 0.828 0.000 NA 0.072
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4063 0.62307 0.252 0.000 0.712 0.000 NA 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3653 0.70115 0.000 0.692 0.000 0.008 NA 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.1155 0.63057 0.956 0.000 0.036 0.000 NA 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3586 0.74200 0.000 0.756 0.000 0.028 NA 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5953 0.28168 0.592 0.004 0.072 0.000 NA 0.256
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.6075 0.21216 0.000 0.068 0.000 0.312 NA 0.536
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.1970 0.60645 0.900 0.000 0.092 0.000 NA 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.2954 0.83104 0.000 0.048 0.000 0.852 NA 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.5065 0.61806 0.000 0.636 0.000 0.172 NA 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5195 0.58791 0.000 0.540 0.000 0.084 NA 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2805 0.75453 0.000 0.812 0.000 0.004 NA 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.4468 0.59311 0.000 0.732 0.004 0.148 NA 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3595 0.73379 0.000 0.704 0.000 0.008 NA 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.3755 0.65266 0.172 0.000 0.032 0.000 NA 0.780
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0547 0.76549 0.000 0.980 0.000 0.000 NA 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.2890 0.70914 0.096 0.000 0.000 0.032 NA 0.860
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.1204 0.75660 0.000 0.944 0.000 0.000 NA 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.5869 0.37038 0.568 0.000 0.292 0.000 NA 0.080
#> EE97212E-8D5D-4548-8DD2-317049601FDB 6 0.4540 0.64888 0.216 0.000 0.004 0.000 NA 0.696
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2602 0.63769 0.884 0.000 0.024 0.000 NA 0.072
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1285 0.62751 0.944 0.000 0.052 0.000 NA 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4329 0.66703 0.232 0.000 0.712 0.000 NA 0.040
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2871 0.75069 0.000 0.804 0.000 0.004 NA 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0405 0.84833 0.000 0.008 0.000 0.988 NA 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2544 0.60834 0.864 0.000 0.120 0.000 NA 0.012
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3269 0.50870 0.792 0.000 0.184 0.000 NA 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.7129 0.03678 0.000 0.336 0.000 0.356 NA 0.084
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 6 0.5927 0.31585 0.004 0.260 0.000 0.008 NA 0.536
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.6463 0.13035 0.336 0.000 0.436 0.000 NA 0.196
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2933 0.70805 0.108 0.000 0.000 0.032 NA 0.852
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0260 0.84842 0.000 0.008 0.000 0.992 NA 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1546 0.63956 0.944 0.000 0.020 0.000 NA 0.020
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4566 0.18907 0.596 0.000 0.004 0.000 NA 0.364
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1714 0.76498 0.000 0.908 0.000 0.000 NA 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.4945 0.57954 0.092 0.000 0.068 0.000 NA 0.724
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 6 0.7677 -0.16873 0.000 0.276 0.000 0.216 NA 0.296
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3298 0.68571 0.236 0.000 0.756 0.000 NA 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.4568 0.57738 0.000 0.724 0.012 0.152 NA 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.4476 0.60180 0.268 0.000 0.008 0.000 NA 0.676
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3023 0.60295 0.864 0.000 0.052 0.000 NA 0.028
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.3867 0.70757 0.000 0.660 0.000 0.012 NA 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.6325 0.24461 0.512 0.000 0.152 0.000 NA 0.288
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3645 0.55638 0.784 0.000 0.176 0.000 NA 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2915 0.75539 0.000 0.808 0.000 0.008 NA 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.3509 0.43460 0.744 0.000 0.240 0.000 NA 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.5025 0.34974 0.408 0.000 0.000 0.012 NA 0.532
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.3631 0.63761 0.036 0.004 0.012 0.008 NA 0.820
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2793 0.76686 0.000 0.800 0.000 0.000 NA 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.5714 0.61332 0.000 0.560 0.000 0.160 NA 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.3979 0.38640 0.708 0.000 0.256 0.000 NA 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.4546 0.71102 0.000 0.692 0.000 0.104 NA 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0993 0.63840 0.964 0.000 0.012 0.000 NA 0.024
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0865 0.76321 0.000 0.964 0.000 0.000 NA 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.3456 0.68550 0.172 0.000 0.000 0.000 NA 0.788
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.2152 0.61802 0.904 0.000 0.004 0.000 NA 0.068
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6650 0.20628 0.448 0.000 0.320 0.000 NA 0.176
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3489 0.64057 0.288 0.000 0.708 0.000 NA 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3874 0.68772 0.000 0.636 0.000 0.008 NA 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 6 0.6966 0.29601 0.292 0.004 0.068 0.000 NA 0.436
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5700 0.33732 0.588 0.000 0.276 0.000 NA 0.096
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.5515 0.55702 0.280 0.000 0.036 0.020 NA 0.620
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.3230 0.74367 0.000 0.776 0.000 0.012 NA 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7706 0.19435 0.028 0.356 0.060 0.012 NA 0.204
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0790 0.76873 0.000 0.968 0.000 0.000 NA 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.1610 0.74493 0.000 0.916 0.000 0.000 NA 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.5230 0.20168 0.580 0.000 0.344 0.004 NA 0.020
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0260 0.84842 0.000 0.008 0.000 0.992 NA 0.000
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#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.6178 0.41357 0.008 0.504 0.000 0.008 NA 0.252
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.3237 0.73196 0.000 0.828 0.000 0.020 NA 0.020
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.5290 0.65127 0.000 0.612 0.000 0.152 NA 0.004
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.6878 0.18628 0.000 0.300 0.000 0.412 NA 0.060
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.3465 0.74480 0.000 0.828 0.056 0.000 NA 0.020
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 6 0.3134 0.69830 0.168 0.000 0.000 0.024 NA 0.808
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 6 0.2887 0.70857 0.104 0.000 0.000 0.032 NA 0.856
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.5531 0.07133 0.516 0.000 0.052 0.000 NA 0.392
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 6 0.3773 0.67319 0.204 0.000 0.000 0.000 NA 0.752
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.2848 0.70399 0.160 0.000 0.828 0.000 NA 0.004
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.3039 0.75411 0.000 0.848 0.000 0.060 NA 0.004
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.4091 0.61962 0.000 0.520 0.000 0.008 NA 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0937 0.76004 0.000 0.960 0.000 0.000 NA 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.4799 0.56291 0.000 0.684 0.004 0.172 NA 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.0260 0.84842 0.000 0.008 0.000 0.992 NA 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.4452 0.53621 0.760 0.000 0.060 0.000 NA 0.124
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0713 0.63683 0.972 0.000 0.000 0.000 NA 0.028
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 6 0.4339 0.59150 0.044 0.000 0.068 0.000 NA 0.768
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.1556 0.74672 0.000 0.920 0.000 0.000 NA 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.1584 0.62067 0.928 0.000 0.064 0.000 NA 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 6 0.3963 0.67599 0.208 0.000 0.000 0.028 NA 0.748
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.2597 0.55526 0.824 0.000 0.000 0.000 NA 0.176
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 6 0.3933 0.64029 0.248 0.000 0.000 0.000 NA 0.716
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 6 0.4269 0.57123 0.316 0.000 0.000 0.000 NA 0.648
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.2838 0.71699 0.188 0.000 0.808 0.000 NA 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.2838 0.71557 0.188 0.000 0.808 0.000 NA 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.2425 0.83837 0.000 0.024 0.000 0.884 NA 0.004
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 6 0.4691 0.60096 0.016 0.060 0.016 0.044 NA 0.780
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 6 0.4077 0.59513 0.036 0.000 0.068 0.000 NA 0.788
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4533 0.69651 0.000 0.748 0.036 0.084 NA 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 6 0.2100 0.70627 0.112 0.000 0.000 0.004 NA 0.884
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.4209 0.53093 0.740 0.000 0.196 0.000 NA 0.048
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.4751 0.10059 0.560 0.000 0.392 0.000 NA 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A 6 0.3389 0.70063 0.108 0.000 0.000 0.008 NA 0.824
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 6 0.6495 0.07315 0.368 0.000 0.172 0.000 NA 0.420
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.6057 0.04257 0.544 0.008 0.024 0.004 NA 0.312
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.5865 -0.05631 0.464 0.000 0.060 0.000 NA 0.420
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.5071 0.69055 0.000 0.616 0.000 0.068 NA 0.016
#> 72DDC907-0901-4E61-83CF-38500D03FABC 6 0.6095 0.35338 0.000 0.096 0.000 0.160 NA 0.608
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.5838 0.58820 0.000 0.648 0.148 0.052 NA 0.012
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0865 0.77132 0.000 0.964 0.000 0.000 NA 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 6 0.4044 0.58502 0.312 0.000 0.012 0.000 NA 0.668
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.4460 0.67696 0.000 0.736 0.004 0.008 NA 0.092
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.5077 0.29535 0.600 0.000 0.328 0.000 NA 0.028
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.2058 0.71834 0.072 0.000 0.908 0.000 NA 0.008
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 6 0.3987 0.59625 0.036 0.000 0.068 0.000 NA 0.796
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.2778 0.76740 0.000 0.824 0.000 0.008 NA 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.1926 0.84301 0.000 0.020 0.000 0.912 NA 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4416 0.41963 0.680 0.000 0.008 0.000 NA 0.268
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.5166 0.29974 0.604 0.000 0.036 0.000 NA 0.316
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.1387 0.76859 0.000 0.932 0.000 0.000 NA 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4382 0.74434 0.000 0.744 0.000 0.064 NA 0.024
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.6037 0.29916 0.548 0.000 0.100 0.000 NA 0.296
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4545 0.52000 0.344 0.000 0.616 0.000 NA 0.032
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.5168 -0.15590 0.476 0.000 0.456 0.000 NA 0.056
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.2540 0.70927 0.104 0.000 0.000 0.020 NA 0.872
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1075 0.77289 0.000 0.952 0.000 0.000 NA 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.2092 0.77407 0.000 0.876 0.000 0.000 NA 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.2721 0.83626 0.000 0.040 0.000 0.868 NA 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.2964 0.70645 0.204 0.000 0.792 0.000 NA 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 6 0.4132 0.64894 0.212 0.000 0.016 0.000 NA 0.736
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.3351 0.58507 0.808 0.000 0.152 0.000 NA 0.004
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.2520 0.72801 0.152 0.000 0.844 0.000 NA 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2201 0.62898 0.904 0.000 0.056 0.000 NA 0.004
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.4463 0.17182 0.588 0.000 0.376 0.000 NA 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.2808 0.70358 0.060 0.000 0.876 0.000 NA 0.024
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.5614 0.33299 0.412 0.000 0.492 0.000 NA 0.048
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.1141 0.62558 0.948 0.000 0.052 0.000 NA 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0914 0.63632 0.968 0.000 0.016 0.000 NA 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.3874 0.70309 0.000 0.636 0.000 0.008 NA 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.8287 -0.05775 0.032 0.348 0.228 0.020 NA 0.264
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.2444 0.63234 0.896 0.000 0.052 0.000 NA 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.5928 0.44265 0.284 0.000 0.576 0.008 NA 0.040
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.2340 0.58367 0.852 0.000 0.000 0.000 NA 0.148
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.3398 0.72707 0.000 0.740 0.000 0.008 NA 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1714 0.76364 0.000 0.908 0.000 0.000 NA 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.3301 0.70463 0.124 0.000 0.000 0.032 NA 0.828
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1584 0.61804 0.928 0.000 0.064 0.000 NA 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3717 0.64019 0.276 0.000 0.708 0.000 NA 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.4464 0.59484 0.284 0.000 0.000 0.012 NA 0.668
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3956 0.61384 0.788 0.000 0.092 0.000 NA 0.104
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.4310 0.66049 0.000 0.576 0.000 0.016 NA 0.004
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.3592 0.74542 0.000 0.008 0.000 0.808 NA 0.116
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.3210 0.82726 0.000 0.040 0.000 0.844 NA 0.020
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.4624 0.63365 0.244 0.000 0.000 0.024 NA 0.688
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.4093 0.66551 0.000 0.584 0.000 0.012 NA 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.2932 0.70557 0.132 0.000 0.000 0.024 NA 0.840
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.5395 0.13609 0.544 0.000 0.020 0.000 NA 0.364
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4623 0.11916 0.564 0.000 0.400 0.000 NA 0.008
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0260 0.84842 0.000 0.008 0.000 0.992 NA 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4053 0.58593 0.796 0.000 0.068 0.000 NA 0.084
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.3614 0.50502 0.752 0.000 0.220 0.000 NA 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.5791 0.47756 0.000 0.528 0.000 0.252 NA 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.2886 0.76847 0.000 0.836 0.000 0.016 NA 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.6258 0.53017 0.000 0.592 0.076 0.008 NA 0.116
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.3867 0.66067 0.192 0.000 0.008 0.000 NA 0.760
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0260 0.84842 0.000 0.008 0.000 0.992 NA 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.6124 0.00896 0.464 0.000 0.376 0.000 NA 0.128
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.3161 0.59313 0.828 0.000 0.028 0.000 NA 0.136
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3847 0.55209 0.348 0.000 0.644 0.000 NA 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 6 0.6292 0.34631 0.360 0.000 0.100 0.000 NA 0.476
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3298 0.75567 0.000 0.756 0.000 0.008 NA 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.2887 0.70857 0.104 0.000 0.000 0.032 NA 0.856
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4170 0.70902 0.000 0.660 0.000 0.032 NA 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4106 0.58522 0.312 0.000 0.664 0.000 NA 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.1010 0.63005 0.960 0.000 0.036 0.000 NA 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3241 0.61800 0.836 0.000 0.112 0.000 NA 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.4234 0.35688 0.676 0.000 0.280 0.000 NA 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3841 0.73669 0.000 0.724 0.000 0.032 NA 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3260 0.59208 0.824 0.000 0.028 0.000 NA 0.136
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5629 0.37733 0.616 0.000 0.240 0.000 NA 0.100
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.6397 0.26380 0.528 0.000 0.148 0.000 NA 0.260
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2213 0.62481 0.888 0.000 0.008 0.000 NA 0.100
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.2905 0.83230 0.000 0.048 0.000 0.856 NA 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4224 0.43482 0.700 0.000 0.008 0.000 NA 0.256
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2721 0.72926 0.000 0.868 0.040 0.004 NA 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3001 0.70245 0.060 0.000 0.868 0.004 NA 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0713 0.76351 0.000 0.972 0.000 0.000 NA 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0909 0.63749 0.968 0.000 0.012 0.000 NA 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.4681 0.63326 0.232 0.000 0.000 0.000 NA 0.668
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5858 0.41387 0.320 0.000 0.544 0.000 NA 0.096
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.3868 0.25051 0.496 0.000 0.000 0.000 NA 0.504
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.673 0.871 0.935 0.5000 0.500 0.500
#> 3 3 0.723 0.808 0.910 0.3263 0.694 0.463
#> 4 4 0.536 0.593 0.787 0.0796 0.742 0.406
#> 5 5 0.587 0.559 0.774 0.0877 0.873 0.591
#> 6 6 0.660 0.531 0.759 0.0384 0.885 0.565
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9282 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.1843 0.9190 0.972 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.1843 0.9246 0.028 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.9970 0.2025 0.468 0.532
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.9970 0.0458 0.532 0.468
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.5629 0.8367 0.132 0.868
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.1633 0.9257 0.024 0.976
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1414 0.9255 0.980 0.020
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.6343 0.8272 0.160 0.840
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.1843 0.9246 0.028 0.972
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0376 0.9279 0.004 0.996
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5178 0.8612 0.884 0.116
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.6148 0.8277 0.152 0.848
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0376 0.9307 0.996 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0938 0.9268 0.988 0.012
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.7453 0.7624 0.788 0.212
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.1843 0.9190 0.972 0.028
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0672 0.9273 0.008 0.992
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.6531 0.8112 0.168 0.832
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9282 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.9282 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1184 0.9249 0.016 0.984
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9311 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0376 0.9279 0.004 0.996
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9311 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9282 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.2236 0.9211 0.036 0.964
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.1633 0.9212 0.976 0.024
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.5178 0.8612 0.884 0.116
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1414 0.9255 0.980 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.3274 0.9041 0.940 0.060
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9282 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.9850 0.3275 0.428 0.572
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1184 0.9271 0.984 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.9732 0.3964 0.596 0.404
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.1843 0.9190 0.972 0.028
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.1414 0.9234 0.980 0.020
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0938 0.9281 0.988 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9311 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.6048 0.8316 0.148 0.852
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1414 0.9255 0.980 0.020
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.9311 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9282 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9311 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.1843 0.9190 0.972 0.028
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.1843 0.9246 0.028 0.972
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.9282 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.1184 0.9250 0.984 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.9248 0.5499 0.660 0.340
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.5842 0.8394 0.140 0.860
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0376 0.9304 0.996 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.6148 0.8285 0.848 0.152
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0938 0.9262 0.012 0.988
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.9896 0.2916 0.560 0.440
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9311 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1414 0.9231 0.980 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9282 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.1843 0.9190 0.972 0.028
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.2043 0.9229 0.032 0.968
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.6531 0.8112 0.168 0.832
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1184 0.9268 0.984 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.5946 0.8357 0.144 0.856
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9311 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0376 0.9304 0.996 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6438 0.8214 0.836 0.164
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.1843 0.9246 0.028 0.972
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.9282 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.9311 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0938 0.9281 0.988 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.9311 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1184 0.9249 0.016 0.984
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.1184 0.9273 0.016 0.984
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0672 0.9273 0.008 0.992
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.9282 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.1843 0.9246 0.028 0.972
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.7602 0.7054 0.780 0.220
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.2603 0.9163 0.044 0.956
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0000 0.9282 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.6343 0.8224 0.840 0.160
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.1633 0.9257 0.024 0.976
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.9311 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.9282 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.9311 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.1414 0.9267 0.020 0.980
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.9311 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.9282 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9311 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.1843 0.9246 0.028 0.972
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.9311 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4815 0.8722 0.104 0.896
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.9311 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.6247 0.8250 0.844 0.156
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0000 0.9311 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2603 0.9122 0.044 0.956
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.9311 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0376 0.9279 0.004 0.996
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.6712 0.8028 0.176 0.824
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.9282 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.2423 0.9132 0.960 0.040
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1633 0.9220 0.024 0.976
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.9311 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.9311 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.3274 0.9104 0.060 0.940
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.9282 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0376 0.9304 0.996 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.1843 0.9246 0.028 0.972
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.2603 0.9081 0.956 0.044
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.6623 0.8088 0.828 0.172
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0376 0.9279 0.004 0.996
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.9311 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.1843 0.9190 0.972 0.028
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.4022 0.8827 0.920 0.080
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0672 0.9273 0.008 0.992
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.7528 0.7572 0.784 0.216
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.7056 0.7502 0.808 0.192
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0672 0.9273 0.008 0.992
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 2 0.7745 0.7029 0.228 0.772
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1414 0.9236 0.020 0.980
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.9775 0.3663 0.588 0.412
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0376 0.9304 0.996 0.004
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0000 0.9311 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.9311 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.8267 0.6932 0.260 0.740
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 2 0.1843 0.9246 0.028 0.972
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0000 0.9282 0.000 1.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.1414 0.9231 0.980 0.020
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.1633 0.9212 0.976 0.024
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.9170 0.5661 0.668 0.332
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.9311 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.0000 0.9282 0.000 1.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.4022 0.8902 0.920 0.080
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0672 0.9273 0.008 0.992
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.3584 0.9012 0.932 0.068
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.7219 0.7769 0.800 0.200
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.0000 0.9311 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 2 0.1843 0.9246 0.028 0.972
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.1843 0.9190 0.972 0.028
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.5519 0.8507 0.128 0.872
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.0000 0.9311 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.9282 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 2 0.1843 0.9246 0.028 0.972
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 1 0.9896 0.2936 0.560 0.440
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.9282 0.000 1.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.9282 0.000 1.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.0000 0.9311 1.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.9282 0.000 1.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0672 0.9273 0.008 0.992
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0376 0.9304 0.996 0.004
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 2 0.1843 0.9246 0.028 0.972
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.0000 0.9311 1.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.9282 0.000 1.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 2 0.1843 0.9246 0.028 0.972
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 2 0.2043 0.9229 0.032 0.968
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.0000 0.9311 1.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 2 0.2043 0.9229 0.032 0.968
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.0376 0.9304 0.996 0.004
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.0000 0.9311 1.000 0.000
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 1 0.2423 0.9163 0.960 0.040
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F 2 0.6887 0.7788 0.184 0.816
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0 2 0.0000 0.9282 0.000 1.000
#> D149276E-A961-49D6-8BDA-004E8264A0A1 1 0.0376 0.9304 0.996 0.004
#> D17803A2-4BF2-4382-A544-76E28695214F 1 0.0000 0.9311 1.000 0.000
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6 1 0.0938 0.9281 0.988 0.012
#> 16F5BF94-5103-4973-9432-34FDCC82B6A2 1 0.0000 0.9311 1.000 0.000
#> 293FB23D-72CB-4211-B4ED-9C57412CE9F0 1 0.0376 0.9304 0.996 0.004
#> C99F0CD0-B9EB-45F3-885F-6D0519BF1BF7 2 0.1414 0.9236 0.020 0.980
#> 5B8D1101-572C-4445-81C4-83A6D6115451 1 0.0000 0.9311 1.000 0.000
#> CA86A053-8669-43F5-947A-9D6D368E7087 1 0.6623 0.8087 0.828 0.172
#> FDDECB98-0151-4207-BC4E-040E121703DB 1 0.0376 0.9304 0.996 0.004
#> 862D2F88-77A9-4363-A744-7738F49980E8 1 0.0000 0.9311 1.000 0.000
#> E65849D9-E4E6-4706-8A7C-EBF07E80C0D9 1 0.1843 0.9190 0.972 0.028
#> C8820FA6-3531-4515-A102-19100775E767 1 0.1843 0.9190 0.972 0.028
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#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9282 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.9282 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.0000 0.9311 1.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.1843 0.9202 0.028 0.972
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.1843 0.9246 0.028 0.972
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0000 0.9311 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.1633 0.9220 0.024 0.976
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.9311 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 2 0.9686 0.3127 0.396 0.604
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0000 0.9311 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.4939 0.8678 0.108 0.892
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.0000 0.9311 1.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.6623 0.8088 0.828 0.172
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.1843 0.9246 0.028 0.972
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.6247 0.8239 0.156 0.844
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.1184 0.9249 0.016 0.984
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0376 0.9279 0.004 0.996
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 2 0.5294 0.8527 0.120 0.880
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.6048 0.8132 0.852 0.148
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 1 0.9209 0.4728 0.664 0.336
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.7376 0.7655 0.208 0.792
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.1843 0.9190 0.972 0.028
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.9282 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.9311 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.9311 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.0000 0.9311 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.9311 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.1843 0.9246 0.028 0.972
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.7745 0.7392 0.228 0.772
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.9282 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0376 0.9279 0.004 0.996
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9282 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.1633 0.9213 0.976 0.024
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.6623 0.8090 0.828 0.172
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0376 0.9304 0.996 0.004
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9311 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9282 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.3274 0.9041 0.940 0.060
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9311 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9311 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.9311 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9311 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.2043 0.9229 0.032 0.968
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.8555 0.6112 0.280 0.720
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.1843 0.9190 0.972 0.028
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.9311 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9311 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0938 0.9277 0.012 0.988
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.9311 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.1633 0.9240 0.976 0.024
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.9393 0.5143 0.644 0.356
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.9311 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.9311 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.5408 0.8549 0.876 0.124
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9311 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.1843 0.9190 0.972 0.028
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.1843 0.9190 0.972 0.028
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.1414 0.9265 0.020 0.980
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.4161 0.8863 0.084 0.916
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0376 0.9304 0.996 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.9282 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.9323 0.5328 0.652 0.348
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.1843 0.9246 0.028 0.972
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9311 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0376 0.9279 0.004 0.996
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.1843 0.9190 0.972 0.028
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9311 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.0672 0.9299 0.992 0.008
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9282 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.8861 0.5466 0.696 0.304
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9311 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.8081 0.7125 0.752 0.248
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0376 0.9304 0.996 0.004
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9311 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0938 0.9262 0.012 0.988
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9282 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2043 0.9172 0.968 0.032
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 1.0000 -0.0676 0.496 0.504
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9311 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.9970 0.1979 0.532 0.468
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.1843 0.9246 0.028 0.972
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.5737 0.8434 0.864 0.136
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.1843 0.9246 0.028 0.972
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.1843 0.9246 0.028 0.972
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1184 0.9268 0.984 0.016
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.2043 0.9202 0.968 0.032
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0376 0.9304 0.996 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.9754 0.3841 0.408 0.592
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.6887 0.7943 0.184 0.816
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4815 0.8717 0.896 0.104
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.1633 0.9257 0.024 0.976
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9311 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0376 0.9279 0.004 0.996
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0672 0.9273 0.008 0.992
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9311 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.6048 0.8321 0.852 0.148
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.7056 0.7590 0.192 0.808
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9311 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1184 0.9271 0.984 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.8713 0.6396 0.292 0.708
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1414 0.9231 0.980 0.020
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.1843 0.9190 0.972 0.028
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9311 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.6973 0.7892 0.188 0.812
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9311 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9311 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6801 0.8010 0.820 0.180
#> 1122039D-5785-4F70-9916-17C585453512 2 0.4431 0.8800 0.092 0.908
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.2948 0.9092 0.948 0.052
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.7883 0.7301 0.764 0.236
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.5629 0.8466 0.132 0.868
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.9087 0.5801 0.324 0.676
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.4022 0.8901 0.080 0.920
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.1633 0.9212 0.976 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.7056 0.7993 0.192 0.808
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0376 0.9304 0.996 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9311 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.1843 0.9246 0.028 0.972
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.9311 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.6438 0.8157 0.164 0.836
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9311 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.9754 0.3857 0.408 0.592
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.8386 0.6815 0.732 0.268
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2778 0.9115 0.952 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.6531 0.8130 0.832 0.168
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.2423 0.9186 0.040 0.960
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.6048 0.8315 0.148 0.852
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9311 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2603 0.9140 0.956 0.044
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9311 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9311 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.1843 0.9190 0.972 0.028
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0376 0.9304 0.996 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9282 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.1633 0.9257 0.024 0.976
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0938 0.9262 0.012 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0938 0.9285 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1633 0.9212 0.976 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0376 0.9304 0.996 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9311 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 3 0.5178 0.63807 0.000 0.256 0.744
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.2448 0.85606 0.076 0.924 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.87071 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0237 0.89758 0.004 0.996 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0237 0.89758 0.004 0.996 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0592 0.87011 0.012 0.000 0.988
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.7960 0.56419 0.120 0.648 0.232
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1753 0.91082 0.952 0.000 0.048
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3686 0.78278 0.140 0.000 0.860
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.87071 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0747 0.89628 0.000 0.984 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3816 0.82447 0.852 0.000 0.148
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.89844 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.2066 0.90379 0.940 0.000 0.060
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6192 0.22483 0.580 0.420 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.4504 0.72368 0.196 0.000 0.804
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.4002 0.78151 0.160 0.840 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0424 0.89801 0.000 0.992 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.89844 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2625 0.85632 0.000 0.916 0.084
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.2959 0.80477 0.000 0.100 0.900
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0237 0.89848 0.000 0.996 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.92532 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1163 0.89168 0.000 0.972 0.028
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0592 0.91928 0.988 0.012 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.6299 0.09451 0.000 0.524 0.476
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0237 0.87088 0.004 0.000 0.996
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0592 0.92081 0.988 0.012 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3192 0.86290 0.888 0.000 0.112
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2066 0.90375 0.940 0.000 0.060
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5678 0.58267 0.684 0.000 0.316
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1411 0.88806 0.000 0.964 0.036
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0592 0.89518 0.012 0.988 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2261 0.89801 0.932 0.000 0.068
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.1529 0.86215 0.040 0.000 0.960
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.5327 0.65061 0.272 0.728 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.5882 0.51302 0.348 0.652 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.1753 0.91067 0.952 0.000 0.048
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.92532 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.0237 0.89758 0.004 0.996 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1411 0.91670 0.964 0.000 0.036
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#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0237 0.89758 0.004 0.996 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.5098 0.66717 0.000 0.752 0.248
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.1163 0.89168 0.000 0.972 0.028
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0892 0.89487 0.000 0.980 0.020
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 2 0.5926 0.47119 0.356 0.644 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.6541 0.55975 0.672 0.024 0.304
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0592 0.92573 0.988 0.000 0.012
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.92532 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.6062 0.40447 0.000 0.616 0.384
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.2878 0.87660 0.904 0.000 0.096
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.92532 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0237 0.92610 0.996 0.000 0.004
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.92532 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0237 0.92610 0.996 0.000 0.004
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0237 0.87088 0.004 0.000 0.996
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.1529 0.86245 0.040 0.000 0.960
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.1411 0.88357 0.036 0.964 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.1411 0.90275 0.964 0.036 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.92532 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.5785 0.50839 0.000 0.668 0.332
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0237 0.92375 0.996 0.004 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.2537 0.89049 0.920 0.000 0.080
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.1411 0.86377 0.036 0.000 0.964
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0237 0.92375 0.996 0.004 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1031 0.92234 0.976 0.000 0.024
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.5634 0.78235 0.800 0.056 0.144
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0237 0.92610 0.996 0.000 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0592 0.89509 0.012 0.988 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.5706 0.50157 0.680 0.320 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.1753 0.84369 0.000 0.048 0.952
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.89844 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0237 0.92610 0.996 0.000 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.3879 0.79413 0.000 0.848 0.152
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.1529 0.86215 0.040 0.000 0.960
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.87071 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0237 0.92375 0.996 0.004 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0237 0.89848 0.000 0.996 0.004
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.2878 0.83852 0.096 0.904 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0237 0.92610 0.996 0.000 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.1860 0.90831 0.948 0.000 0.052
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 3 0.6168 0.31508 0.000 0.412 0.588
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0237 0.89758 0.004 0.996 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0424 0.92611 0.992 0.000 0.008
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.1529 0.86239 0.040 0.000 0.960
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.3551 0.84450 0.868 0.000 0.132
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0237 0.92375 0.996 0.004 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0424 0.89801 0.000 0.992 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.2261 0.86954 0.000 0.932 0.068
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.0747 0.89351 0.016 0.984 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0892 0.86850 0.020 0.000 0.980
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.92532 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.1411 0.86459 0.036 0.000 0.964
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.87071 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.4842 0.72587 0.776 0.000 0.224
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0237 0.87088 0.004 0.000 0.996
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0237 0.86948 0.000 0.004 0.996
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.3038 0.87063 0.896 0.000 0.104
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.1964 0.90611 0.944 0.000 0.056
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0892 0.92379 0.980 0.000 0.020
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.89844 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.4555 0.72675 0.000 0.800 0.200
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5733 0.55283 0.676 0.000 0.324
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0237 0.86948 0.000 0.004 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0237 0.92610 0.996 0.000 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0424 0.89801 0.000 0.992 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0237 0.89848 0.000 0.996 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.92532 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.5497 0.61262 0.708 0.000 0.292
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0892 0.86850 0.020 0.000 0.980
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.92532 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.2066 0.90370 0.940 0.000 0.060
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.89844 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.2878 0.84779 0.904 0.096 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.5926 0.41260 0.644 0.356 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.92532 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.89844 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.92532 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0237 0.92610 0.996 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3192 0.81335 0.112 0.000 0.888
#> 1122039D-5785-4F70-9916-17C585453512 2 0.4521 0.74651 0.004 0.816 0.180
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.3619 0.83883 0.864 0.000 0.136
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.1964 0.85501 0.056 0.000 0.944
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.89844 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.89844 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.3038 0.84231 0.000 0.896 0.104
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0237 0.92375 0.996 0.004 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.5850 0.71370 0.040 0.772 0.188
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0424 0.92611 0.992 0.000 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0592 0.92573 0.988 0.000 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.87071 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0237 0.92610 0.996 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.89844 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0237 0.92375 0.996 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.89844 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1860 0.85705 0.052 0.000 0.948
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2066 0.90379 0.940 0.000 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.4887 0.68499 0.228 0.000 0.772
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0237 0.87088 0.004 0.000 0.996
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.89844 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0747 0.92501 0.984 0.000 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2448 0.89230 0.924 0.000 0.076
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0747 0.92501 0.984 0.000 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0237 0.92610 0.996 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.1289 0.88564 0.032 0.968 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0237 0.92610 0.996 0.000 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6111 0.30834 0.000 0.396 0.604
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0237 0.86948 0.000 0.004 0.996
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1031 0.89332 0.000 0.976 0.024
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1031 0.92227 0.976 0.000 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0829 0.92265 0.984 0.012 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0892 0.92379 0.980 0.000 0.020
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0237 0.92610 0.996 0.000 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4631 0.660504 0.260 0.728 0.004 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4360 0.467561 0.000 0.248 0.008 0.744
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4193 0.697088 0.268 0.000 0.732 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5093 0.280206 0.000 0.348 0.012 0.640
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1940 0.825142 0.000 0.924 0.000 0.076
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.2704 0.653163 0.876 0.000 0.124 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.7427 0.291099 0.044 0.488 0.404 0.064
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2814 0.731241 0.868 0.000 0.000 0.132
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.4933 -0.297154 0.568 0.000 0.432 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2868 0.696680 0.136 0.000 0.864 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2799 0.806345 0.108 0.884 0.000 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2149 0.733110 0.912 0.000 0.000 0.088
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1637 0.829053 0.000 0.940 0.000 0.060
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.3612 0.649051 0.856 0.100 0.000 0.044
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1867 0.607751 0.000 0.072 0.000 0.928
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0804 0.714076 0.980 0.008 0.000 0.012
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4164 0.448468 0.000 0.264 0.000 0.736
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.1389 0.833176 0.000 0.952 0.000 0.048
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1389 0.835317 0.000 0.952 0.000 0.048
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2480 0.815870 0.088 0.904 0.000 0.008
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.695056 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1022 0.837316 0.000 0.968 0.000 0.032
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.4817 0.194325 0.388 0.000 0.000 0.612
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0895 0.840035 0.004 0.976 0.000 0.020
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.1637 0.634257 0.060 0.000 0.000 0.940
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.5473 0.664317 0.084 0.724 0.192 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4999 -0.178949 0.492 0.000 0.508 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6561 0.409877 0.564 0.092 0.000 0.344
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3808 0.718792 0.812 0.000 0.012 0.176
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2408 0.733483 0.896 0.000 0.000 0.104
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5267 0.701628 0.740 0.000 0.076 0.184
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2048 0.826572 0.064 0.928 0.000 0.008
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4868 0.371824 0.000 0.304 0.012 0.684
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1867 0.732007 0.928 0.000 0.000 0.072
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0992 0.705495 0.976 0.008 0.012 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.3486 0.545980 0.000 0.188 0.000 0.812
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4907 0.323454 0.000 0.580 0.000 0.420
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.6337 0.130625 0.380 0.000 0.068 0.552
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.1716 0.633222 0.064 0.000 0.000 0.936
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.6980 0.215663 0.000 0.132 0.332 0.536
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.2216 0.734889 0.908 0.000 0.000 0.092
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3219 0.726058 0.836 0.000 0.000 0.164
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1209 0.839750 0.032 0.964 0.000 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.4999 -0.160153 0.492 0.000 0.000 0.508
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.2589 0.590540 0.000 0.116 0.000 0.884
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.2011 0.713151 0.080 0.000 0.920 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0000 0.695056 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.4643 0.310645 0.344 0.000 0.000 0.656
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3540 0.656811 0.876 0.064 0.048 0.012
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0336 0.840010 0.000 0.992 0.000 0.008
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.4746 0.541946 0.632 0.000 0.000 0.368
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3833 0.726156 0.848 0.000 0.080 0.072
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.5594 0.649908 0.000 0.716 0.092 0.192
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.2345 0.677702 0.900 0.000 0.100 0.000
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#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0336 0.839672 0.000 0.992 0.000 0.008
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.3219 0.547919 0.836 0.000 0.164 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.1174 0.837843 0.020 0.968 0.000 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.3024 0.778224 0.000 0.852 0.000 0.148
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.3024 0.778553 0.000 0.852 0.000 0.148
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.3649 0.527932 0.000 0.204 0.000 0.796
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.4285 0.755654 0.104 0.820 0.076 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 4 0.4955 -0.022593 0.444 0.000 0.000 0.556
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.1557 0.634887 0.056 0.000 0.000 0.944
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.3219 0.726108 0.836 0.000 0.000 0.164
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.4981 0.308286 0.536 0.000 0.000 0.464
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.4585 0.656493 0.332 0.000 0.668 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4134 0.650342 0.000 0.740 0.000 0.260
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.3196 0.802908 0.104 0.876 0.012 0.008
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.2186 0.835886 0.012 0.932 0.008 0.048
#> 80936433-AA91-4219-98F1-706C36298060 2 0.3144 0.809610 0.000 0.884 0.044 0.072
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.3143 0.579821 0.000 0.100 0.024 0.876
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.3400 0.577525 0.856 0.128 0.004 0.012
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4331 0.642407 0.712 0.000 0.000 0.288
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.4761 0.239239 0.372 0.000 0.000 0.628
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.5229 0.217619 0.008 0.428 0.564 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.2530 0.733400 0.888 0.000 0.000 0.112
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.4866 0.126711 0.404 0.000 0.000 0.596
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.4500 0.601767 0.684 0.000 0.000 0.316
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.4888 0.441821 0.588 0.000 0.000 0.412
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.4250 0.658662 0.724 0.000 0.000 0.276
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.1389 0.689104 0.048 0.000 0.952 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5028 0.584212 0.400 0.000 0.596 0.004
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.4957 0.340720 0.000 0.320 0.012 0.668
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.6724 0.405337 0.192 0.192 0.000 0.616
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.4916 0.092859 0.424 0.000 0.000 0.576
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.5008 0.642399 0.016 0.716 0.260 0.008
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.3444 0.557995 0.184 0.000 0.000 0.816
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.3074 0.728939 0.848 0.000 0.000 0.152
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.2799 0.680113 0.884 0.000 0.108 0.008
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.4855 0.276057 0.352 0.004 0.000 0.644
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.3311 0.724805 0.828 0.000 0.000 0.172
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.4063 0.511129 0.808 0.172 0.004 0.016
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.4564 0.331911 0.328 0.000 0.000 0.672
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.1474 0.835354 0.000 0.948 0.000 0.052
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.2011 0.605530 0.000 0.080 0.000 0.920
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.1411 0.697440 0.020 0.020 0.960 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.2408 0.808360 0.000 0.896 0.000 0.104
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4972 0.346634 0.544 0.000 0.000 0.456
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.4785 0.774369 0.108 0.812 0.052 0.028
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.1743 0.688719 0.940 0.000 0.056 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3679 0.701168 0.084 0.000 0.856 0.060
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.2921 0.606890 0.140 0.000 0.000 0.860
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0672 0.840088 0.008 0.984 0.000 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.4019 0.520498 0.000 0.196 0.012 0.792
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4817 0.506351 0.612 0.000 0.000 0.388
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.2216 0.733276 0.908 0.000 0.000 0.092
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.3727 0.764163 0.164 0.824 0.004 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.3074 0.778117 0.000 0.848 0.000 0.152
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4925 0.424220 0.572 0.000 0.000 0.428
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2675 0.673819 0.100 0.000 0.892 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.5403 0.547512 0.628 0.000 0.024 0.348
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.3123 0.583551 0.156 0.000 0.000 0.844
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1022 0.837316 0.000 0.968 0.000 0.032
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.1722 0.832894 0.048 0.944 0.000 0.008
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.5018 0.316536 0.000 0.332 0.012 0.656
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0921 0.702533 0.028 0.000 0.972 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 4 0.3444 0.557683 0.184 0.000 0.000 0.816
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1994 0.667249 0.936 0.052 0.004 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.695056 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1816 0.705144 0.948 0.024 0.004 0.024
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.4193 0.301102 0.732 0.000 0.268 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.695056 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4546 0.676830 0.732 0.000 0.012 0.256
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.3172 0.725715 0.840 0.000 0.000 0.160
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3726 0.702997 0.788 0.000 0.000 0.212
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1022 0.839733 0.000 0.968 0.000 0.032
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.7741 0.183635 0.004 0.448 0.204 0.344
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.2282 0.718086 0.924 0.024 0.000 0.052
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4193 0.699056 0.268 0.000 0.732 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4624 0.573462 0.660 0.000 0.000 0.340
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.1807 0.829913 0.052 0.940 0.000 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1489 0.836004 0.004 0.952 0.000 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.3801 0.516567 0.220 0.000 0.000 0.780
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1867 0.732012 0.928 0.000 0.000 0.072
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.4483 0.443169 0.712 0.000 0.284 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.4999 -0.202737 0.492 0.000 0.000 0.508
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.2921 0.730427 0.860 0.000 0.000 0.140
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.1059 0.838836 0.016 0.972 0.000 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0895 0.628692 0.004 0.020 0.000 0.976
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.2334 0.598695 0.000 0.088 0.004 0.908
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.4072 0.472271 0.252 0.000 0.000 0.748
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.1059 0.839736 0.012 0.972 0.000 0.016
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.4431 0.381740 0.304 0.000 0.000 0.696
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.4998 -0.200731 0.488 0.000 0.000 0.512
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.1807 0.700174 0.940 0.000 0.052 0.008
#> 1122039D-5785-4F70-9916-17C585453512 3 0.6396 0.142807 0.000 0.072 0.548 0.380
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.3117 0.727812 0.880 0.028 0.000 0.092
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1486 0.691156 0.960 0.024 0.008 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.3907 0.688027 0.000 0.768 0.000 0.232
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.1305 0.839539 0.004 0.960 0.000 0.036
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.6568 0.657484 0.056 0.692 0.184 0.068
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.2469 0.616141 0.108 0.000 0.000 0.892
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.6257 0.045344 0.000 0.056 0.508 0.436
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.4868 0.524968 0.212 0.000 0.040 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4331 0.642883 0.712 0.000 0.000 0.288
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4830 0.593728 0.392 0.000 0.608 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4761 0.531806 0.628 0.000 0.000 0.372
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1389 0.833275 0.000 0.952 0.000 0.048
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.2216 0.622876 0.092 0.000 0.000 0.908
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0376 0.839884 0.004 0.992 0.000 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4624 0.521654 0.660 0.000 0.340 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2530 0.733346 0.888 0.000 0.000 0.112
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.2156 0.659248 0.928 0.060 0.004 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.3356 0.582523 0.824 0.000 0.176 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1716 0.827366 0.000 0.936 0.000 0.064
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4356 0.633502 0.708 0.000 0.000 0.292
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4372 0.656596 0.728 0.000 0.004 0.268
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4585 0.590594 0.668 0.000 0.000 0.332
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4585 0.587511 0.668 0.000 0.000 0.332
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4522 0.351733 0.000 0.320 0.000 0.680
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4830 0.496020 0.608 0.000 0.000 0.392
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6197 0.153811 0.052 0.440 0.508 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0188 0.696549 0.004 0.000 0.996 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0657 0.840620 0.004 0.984 0.000 0.012
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3448 0.723384 0.828 0.004 0.000 0.168
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4638 0.703501 0.776 0.044 0.000 0.180
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.4817 0.134368 0.388 0.000 0.000 0.612
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4761 0.521523 0.628 0.000 0.000 0.372
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.4503 0.508387 0.036 0.268 0.000 0.000 0.696
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.3586 0.493385 0.000 0.264 0.000 0.736 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2563 0.660706 0.120 0.000 0.872 0.000 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.3906 0.460545 0.000 0.292 0.004 0.704 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1205 0.788404 0.000 0.956 0.000 0.040 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.1787 0.698429 0.936 0.004 0.044 0.000 0.016
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.6306 -0.026433 0.500 0.328 0.172 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4489 0.664169 0.740 0.000 0.000 0.068 0.192
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 5 0.5987 0.233417 0.132 0.000 0.324 0.000 0.544
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.2970 0.587135 0.004 0.000 0.168 0.000 0.828
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.1270 0.663838 0.000 0.052 0.000 0.000 0.948
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2921 0.705049 0.856 0.000 0.000 0.020 0.124
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2491 0.762937 0.000 0.896 0.000 0.036 0.068
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.0963 0.670121 0.036 0.000 0.000 0.000 0.964
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0963 0.688492 0.000 0.036 0.000 0.964 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.1341 0.718865 0.944 0.000 0.000 0.000 0.056
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.3661 0.480597 0.000 0.276 0.000 0.724 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4664 0.158838 0.000 0.552 0.004 0.008 0.436
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1357 0.785206 0.000 0.948 0.000 0.048 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.3177 0.669482 0.000 0.792 0.000 0.000 0.208
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.670430 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0404 0.794070 0.000 0.988 0.000 0.012 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.3958 0.618560 0.176 0.000 0.000 0.780 0.044
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.794494 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.0703 0.710318 0.024 0.000 0.000 0.976 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.6261 0.286633 0.000 0.356 0.156 0.000 0.488
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.4225 0.451437 0.632 0.004 0.364 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.7117 0.118584 0.452 0.116 0.000 0.372 0.060
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0566 0.716294 0.984 0.000 0.000 0.004 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1399 0.726388 0.952 0.000 0.000 0.028 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6615 0.411333 0.484 0.000 0.004 0.216 0.296
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2377 0.746678 0.000 0.872 0.000 0.000 0.128
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#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.6816 0.156574 0.360 0.000 0.000 0.320 0.320
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.4573 0.528569 0.092 0.000 0.000 0.164 0.744
#> EB7883EB-0079-4548-9132-169E94A698BA 5 0.3278 0.606816 0.020 0.000 0.000 0.156 0.824
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3508 0.640482 0.748 0.000 0.000 0.252 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.3949 0.394642 0.000 0.332 0.000 0.668 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3730 0.601855 0.712 0.000 0.000 0.288 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4829 -0.076603 0.000 0.500 0.480 0.000 0.020
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.670430 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0162 0.794424 0.000 0.996 0.000 0.000 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1750 0.729063 0.936 0.000 0.000 0.036 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4204 0.667747 0.756 0.048 0.000 0.196 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.2727 0.684494 0.116 0.000 0.000 0.868 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.3586 0.629544 0.736 0.000 0.000 0.264 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 3 0.5039 -0.00445 0.004 0.172 0.668 0.000 0.152 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.2805 0.65083 0.000 0.184 0.004 0.000 0.000 0.812
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4817 0.13952 0.012 0.000 0.564 0.388 0.036 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 6 0.2714 0.68642 0.000 0.136 0.004 0.000 0.012 0.848
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0862 0.80471 0.000 0.972 0.004 0.000 0.016 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.1075 0.69852 0.952 0.000 0.048 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.7329 -0.10556 0.292 0.360 0.236 0.112 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0881 0.71252 0.972 0.000 0.008 0.000 0.012 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.5335 0.00554 0.008 0.000 0.476 0.080 0.436 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.5721 0.20133 0.008 0.000 0.344 0.508 0.140 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.4734 0.57608 0.000 0.168 0.152 0.000 0.680 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0520 0.71192 0.984 0.000 0.008 0.000 0.008 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1672 0.79417 0.000 0.932 0.004 0.000 0.048 0.016
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.3514 0.55280 0.208 0.004 0.020 0.000 0.768 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.0436 0.77307 0.004 0.004 0.004 0.000 0.000 0.988
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0935 0.71181 0.964 0.000 0.032 0.000 0.004 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.3329 0.59504 0.000 0.236 0.004 0.000 0.004 0.756
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.4226 0.08659 0.000 0.484 0.004 0.000 0.504 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1173 0.80323 0.000 0.960 0.008 0.000 0.016 0.016
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2996 0.67108 0.000 0.772 0.000 0.000 0.228 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.0146 0.72669 0.000 0.000 0.000 0.996 0.000 0.004
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0603 0.80629 0.000 0.980 0.000 0.000 0.016 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.5230 0.42073 0.548 0.000 0.344 0.000 0.000 0.108
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1275 0.80631 0.000 0.956 0.016 0.000 0.016 0.012
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0363 0.77390 0.012 0.000 0.000 0.000 0.000 0.988
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.2747 0.63566 0.000 0.108 0.028 0.000 0.860 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.3965 0.32827 0.604 0.000 0.008 0.388 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.5716 0.46946 0.636 0.124 0.016 0.000 0.024 0.200
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0508 0.71273 0.984 0.000 0.012 0.000 0.000 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0405 0.71255 0.988 0.000 0.008 0.000 0.000 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 5 0.5774 0.24141 0.340 0.000 0.036 0.000 0.536 0.088
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2092 0.76526 0.000 0.876 0.000 0.000 0.124 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 6 0.3650 0.54780 0.000 0.272 0.004 0.000 0.008 0.716
#> C06D8112-0FA0-4607-988D-589D8694743F 5 0.2783 0.60776 0.148 0.000 0.016 0.000 0.836 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1649 0.70358 0.932 0.000 0.036 0.000 0.032 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.3942 0.33757 0.004 0.624 0.004 0.000 0.000 0.368
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3409 0.76372 0.076 0.832 0.076 0.000 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 6 0.1826 0.76713 0.052 0.000 0.000 0.020 0.004 0.924
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.0458 0.77416 0.016 0.000 0.000 0.000 0.000 0.984
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.5201 0.35923 0.000 0.088 0.004 0.592 0.004 0.312
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1364 0.71217 0.952 0.000 0.016 0.000 0.020 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2810 0.60679 0.832 0.004 0.156 0.000 0.000 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1958 0.79258 0.004 0.896 0.100 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 3 0.6306 -0.15084 0.324 0.000 0.380 0.000 0.008 0.288
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.2188 0.80318 0.032 0.912 0.020 0.000 0.000 0.036
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 4 0.0000 0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.0146 0.72669 0.000 0.000 0.000 0.996 0.000 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.1562 0.76333 0.004 0.032 0.024 0.000 0.000 0.940
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.3766 0.05573 0.304 0.012 0.684 0.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0717 0.80702 0.000 0.976 0.008 0.000 0.016 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 5 0.6187 0.13589 0.128 0.000 0.036 0.000 0.456 0.380
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.1387 0.68672 0.932 0.000 0.068 0.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.4890 0.11167 0.000 0.464 0.004 0.492 0.008 0.032
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.1663 0.67541 0.912 0.000 0.088 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.3563 0.45642 0.664 0.000 0.000 0.000 0.000 0.336
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.6371 0.31274 0.444 0.028 0.340 0.000 0.000 0.188
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1531 0.80478 0.004 0.928 0.068 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0748 0.81015 0.004 0.976 0.016 0.000 0.004 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.2398 0.65759 0.876 0.000 0.104 0.000 0.020 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.1321 0.80015 0.000 0.952 0.004 0.000 0.020 0.024
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0508 0.71273 0.984 0.000 0.012 0.000 0.000 0.004
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1194 0.80361 0.000 0.956 0.004 0.000 0.008 0.032
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.2562 0.69607 0.172 0.000 0.000 0.000 0.000 0.828
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.1285 0.70704 0.944 0.000 0.052 0.000 0.000 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.6227 -0.11112 0.240 0.000 0.396 0.008 0.000 0.356
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.0000 0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5659 0.21018 0.000 0.488 0.348 0.000 0.164 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.4159 0.43363 0.588 0.016 0.396 0.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.2912 0.64617 0.844 0.000 0.040 0.000 0.000 0.116
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.0865 0.77266 0.036 0.000 0.000 0.000 0.000 0.964
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1321 0.80166 0.000 0.952 0.004 0.000 0.020 0.024
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.4493 0.19266 0.160 0.132 0.708 0.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1411 0.80955 0.000 0.936 0.060 0.000 0.000 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.7217 0.23088 0.000 0.284 0.188 0.428 0.092 0.008
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.4317 0.31964 0.408 0.004 0.572 0.016 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 6 0.1138 0.76298 0.000 0.012 0.004 0.024 0.000 0.960
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 4 0.4948 0.08034 0.040 0.000 0.436 0.512 0.012 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.1151 0.65881 0.000 0.012 0.032 0.000 0.956 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 4 0.2171 0.68016 0.032 0.000 0.040 0.912 0.000 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 4 0.0777 0.71794 0.000 0.000 0.024 0.972 0.000 0.004
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.3345 0.52033 0.776 0.020 0.204 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.1245 0.65595 0.000 0.032 0.016 0.000 0.952 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1232 0.70750 0.956 0.016 0.024 0.000 0.000 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.5585 0.06052 0.012 0.000 0.484 0.100 0.404 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.0713 0.77374 0.028 0.000 0.000 0.000 0.000 0.972
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.3364 0.71581 0.024 0.780 0.196 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.0937 0.77219 0.040 0.000 0.000 0.000 0.000 0.960
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 4 0.3974 0.41461 0.000 0.000 0.296 0.680 0.024 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 6 0.3468 0.55418 0.284 0.000 0.000 0.000 0.004 0.712
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4246 0.44006 0.020 0.580 0.400 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.5684 0.33549 0.528 0.000 0.000 0.000 0.244 0.228
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.3489 0.40540 0.708 0.004 0.288 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.3819 0.46702 0.624 0.004 0.372 0.000 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2377 0.75055 0.000 0.868 0.004 0.000 0.124 0.004
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0976 0.71259 0.968 0.000 0.008 0.000 0.016 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.4793 0.52878 0.000 0.084 0.288 0.000 0.628 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1552 0.79617 0.000 0.940 0.004 0.000 0.020 0.036
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.4094 0.41172 0.000 0.324 0.024 0.000 0.652 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 6 0.2547 0.72204 0.000 0.036 0.004 0.080 0.000 0.880
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0665 0.80986 0.000 0.980 0.008 0.000 0.008 0.004
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 6 0.2629 0.73715 0.040 0.000 0.000 0.000 0.092 0.868
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 6 0.1814 0.75087 0.100 0.000 0.000 0.000 0.000 0.900
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.5772 0.20222 0.184 0.468 0.348 0.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.5148 0.18743 0.000 0.472 0.468 0.012 0.044 0.004
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 6 0.2854 0.66655 0.208 0.000 0.000 0.000 0.000 0.792
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.0146 0.72630 0.000 0.000 0.004 0.996 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 6 0.0779 0.76931 0.000 0.008 0.000 0.008 0.008 0.976
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0858 0.70409 0.968 0.000 0.028 0.000 0.004 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1615 0.80765 0.004 0.928 0.064 0.000 0.004 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 3 0.6374 -0.14945 0.212 0.000 0.392 0.000 0.020 0.376
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.4274 0.28299 0.008 0.560 0.000 0.000 0.008 0.424
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.1124 0.81022 0.008 0.956 0.036 0.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.3457 0.69389 0.016 0.752 0.232 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.3547 0.51143 0.668 0.000 0.332 0.000 0.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.1148 0.80272 0.000 0.960 0.004 0.000 0.016 0.020
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.1226 0.80025 0.000 0.952 0.004 0.000 0.040 0.004
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.6104 -0.15297 0.336 0.000 0.372 0.000 0.292 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0972 0.80611 0.000 0.964 0.000 0.000 0.008 0.028
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.6059 0.24266 0.312 0.000 0.408 0.000 0.280 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.4460 0.42426 0.568 0.000 0.404 0.000 0.024 0.004
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 6 0.6301 0.17413 0.292 0.000 0.208 0.000 0.024 0.476
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 6 0.1007 0.77201 0.044 0.000 0.000 0.000 0.000 0.956
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.1462 0.80726 0.008 0.936 0.056 0.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 4 0.6590 0.07515 0.060 0.000 0.384 0.412 0.144 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 5 0.5374 0.42864 0.000 0.116 0.380 0.000 0.504 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 6 0.0146 0.77170 0.000 0.004 0.000 0.000 0.000 0.996
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.4768 0.66205 0.068 0.708 0.192 0.000 0.000 0.032
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.0972 0.70343 0.964 0.008 0.028 0.000 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 6 0.1714 0.75434 0.092 0.000 0.000 0.000 0.000 0.908
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#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.4524 0.40498 0.036 0.560 0.404 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.1151 0.70839 0.956 0.000 0.012 0.000 0.032 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.7651 -0.01319 0.008 0.000 0.356 0.292 0.180 0.164
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 6 0.4534 0.41718 0.020 0.000 0.352 0.000 0.016 0.612
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1918 0.79693 0.008 0.904 0.088 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 6 0.0935 0.76290 0.000 0.032 0.004 0.000 0.000 0.964
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.1297 0.70781 0.948 0.000 0.012 0.000 0.000 0.040
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4490 0.14724 0.596 0.012 0.376 0.000 0.004 0.012
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.0972 0.65879 0.000 0.028 0.008 0.000 0.964 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.2547 0.76588 0.000 0.868 0.004 0.000 0.016 0.112
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.3464 0.50672 0.688 0.000 0.000 0.000 0.000 0.312
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 4 0.1341 0.70398 0.028 0.000 0.000 0.948 0.024 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 5 0.7090 0.26847 0.076 0.000 0.272 0.000 0.384 0.268
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.1663 0.75762 0.088 0.000 0.000 0.000 0.000 0.912
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0937 0.81114 0.000 0.960 0.040 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.2144 0.80559 0.004 0.908 0.040 0.000 0.048 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 6 0.3329 0.59526 0.000 0.236 0.004 0.000 0.004 0.756
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 4 0.2070 0.62947 0.100 0.000 0.000 0.892 0.008 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 6 0.3695 0.36621 0.376 0.000 0.000 0.000 0.000 0.624
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.5195 0.40060 0.540 0.000 0.360 0.000 0.100 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 4 0.0260 0.72515 0.000 0.000 0.000 0.992 0.008 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.4432 0.45960 0.600 0.000 0.364 0.000 0.036 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.1531 0.64116 0.004 0.000 0.068 0.000 0.928 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 4 0.0000 0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.6159 -0.09212 0.448 0.000 0.336 0.000 0.012 0.204
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0405 0.71219 0.988 0.000 0.008 0.000 0.000 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0976 0.71200 0.968 0.000 0.008 0.000 0.008 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2389 0.77613 0.008 0.864 0.128 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 6 0.7591 0.09476 0.020 0.252 0.276 0.016 0.048 0.388
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3999 0.33496 0.500 0.000 0.496 0.000 0.000 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4586 0.13256 0.020 0.012 0.560 0.408 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0891 0.70514 0.968 0.008 0.024 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.2537 0.64683 0.000 0.096 0.032 0.000 0.872 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.3052 0.71124 0.004 0.780 0.216 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.2912 0.64760 0.216 0.000 0.000 0.000 0.000 0.784
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0458 0.70922 0.984 0.000 0.016 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.3889 0.53723 0.736 0.000 0.016 0.232 0.016 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.3647 0.38595 0.360 0.000 0.000 0.000 0.000 0.640
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.5300 0.16761 0.452 0.000 0.464 0.000 0.008 0.076
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.4395 0.33535 0.000 0.580 0.396 0.000 0.016 0.008
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.0146 0.77170 0.000 0.004 0.000 0.000 0.000 0.996
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 6 0.0363 0.76948 0.000 0.012 0.000 0.000 0.000 0.988
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.3619 0.47702 0.316 0.000 0.004 0.000 0.000 0.680
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.2151 0.79498 0.000 0.904 0.072 0.000 0.016 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.2416 0.71457 0.156 0.000 0.000 0.000 0.000 0.844
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.2883 0.65499 0.212 0.000 0.000 0.000 0.000 0.788
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 5 0.3247 0.56065 0.156 0.000 0.036 0.000 0.808 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0363 0.72538 0.000 0.000 0.000 0.988 0.000 0.012
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4221 0.43974 0.588 0.000 0.396 0.000 0.008 0.008
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.3053 0.59026 0.168 0.000 0.020 0.000 0.812 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.1951 0.78707 0.000 0.916 0.004 0.000 0.020 0.060
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.4731 0.51230 0.000 0.288 0.032 0.000 0.652 0.028
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.5339 0.23873 0.116 0.312 0.568 0.004 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.3844 0.66555 0.060 0.128 0.004 0.000 0.012 0.796
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0363 0.72448 0.000 0.000 0.000 0.988 0.000 0.012
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.4748 0.01339 0.048 0.000 0.000 0.504 0.000 0.448
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4488 0.58794 0.720 0.000 0.204 0.000 0.052 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.6075 0.35659 0.348 0.000 0.468 0.168 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4254 0.21292 0.624 0.020 0.352 0.000 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0767 0.80952 0.000 0.976 0.008 0.000 0.004 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0632 0.77408 0.024 0.000 0.000 0.000 0.000 0.976
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0976 0.80478 0.000 0.968 0.008 0.000 0.016 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.2257 0.67159 0.876 0.000 0.000 0.116 0.008 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0291 0.71159 0.992 0.000 0.004 0.000 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.6113 -0.22696 0.296 0.000 0.356 0.000 0.348 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.2988 0.60461 0.824 0.000 0.152 0.024 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0862 0.80471 0.000 0.972 0.004 0.000 0.016 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4759 0.50933 0.640 0.000 0.296 0.000 0.052 0.012
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.6192 0.17624 0.416 0.000 0.344 0.000 0.232 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 5 0.2444 0.65102 0.036 0.000 0.016 0.000 0.896 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0458 0.71229 0.984 0.000 0.000 0.000 0.000 0.016
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.3476 0.56795 0.000 0.260 0.004 0.000 0.004 0.732
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0603 0.71252 0.980 0.000 0.004 0.000 0.000 0.016
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 5 0.7255 0.14880 0.000 0.292 0.288 0.056 0.352 0.012
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 4 0.0000 0.72706 0.000 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0717 0.80588 0.000 0.976 0.000 0.000 0.016 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1556 0.69698 0.920 0.000 0.080 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6327 0.12470 0.480 0.060 0.112 0.000 0.000 0.348
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.2315 0.75174 0.084 0.000 0.008 0.000 0.016 0.892
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1320 0.70980 0.948 0.000 0.016 0.000 0.000 0.036
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.368 0.752 0.882 0.2860 0.742 0.742
#> 3 3 0.226 0.537 0.792 0.5095 0.916 0.888
#> 4 4 0.271 0.502 0.748 0.1699 0.874 0.812
#> 5 5 0.283 0.456 0.733 0.1154 0.940 0.893
#> 6 6 0.304 0.466 0.698 0.0866 0.919 0.845
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.3733 0.85340 0.928 0.072
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.87216 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.9393 0.65047 0.356 0.644
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.9815 0.52319 0.420 0.580
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.0672 0.87322 0.992 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.8763 0.43550 0.704 0.296
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.6247 0.75319 0.844 0.156
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.87216 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.8713 0.52974 0.708 0.292
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.5519 0.73678 0.128 0.872
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.6438 0.76386 0.836 0.164
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0376 0.87243 0.996 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 1 0.6438 0.76239 0.836 0.164
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.1184 0.87221 0.984 0.016
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.4939 0.78195 0.892 0.108
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.2778 0.86428 0.952 0.048
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0000 0.87216 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.9850 0.52451 0.428 0.572
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.0672 0.87322 0.992 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 1 0.7139 0.71901 0.804 0.196
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.68050 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 1 0.4298 0.84361 0.912 0.088
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.87216 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.9922 0.45372 0.448 0.552
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.87216 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 1 0.9286 0.38282 0.656 0.344
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.9933 0.47544 0.452 0.548
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2236 0.86844 0.964 0.036
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2603 0.85029 0.956 0.044
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.87216 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6801 0.75427 0.820 0.180
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 1 0.7139 0.71901 0.804 0.196
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.9087 0.67612 0.324 0.676
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#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.87216 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 1 0.3431 0.85672 0.936 0.064
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.87216 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.4690 0.83107 0.900 0.100
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.5178 0.80039 0.884 0.116
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.87216 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1184 0.87347 0.984 0.016
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0938 0.87270 0.988 0.012
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.4562 0.79644 0.904 0.096
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.2423 0.86475 0.960 0.040
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.0672 0.87320 0.992 0.008
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 1 0.9170 0.43155 0.668 0.332
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 1 0.5946 0.79215 0.856 0.144
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.5519 0.75263 0.872 0.128
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.2423 0.86475 0.960 0.040
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.4939 0.81033 0.892 0.108
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.9209 0.66594 0.336 0.664
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.87216 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 1 0.2423 0.86475 0.960 0.040
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.3733 0.82424 0.928 0.072
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0376 0.87199 0.996 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.2948 0.85937 0.948 0.052
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 1 0.6973 0.73013 0.812 0.188
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.0938 0.87338 0.988 0.012
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.3733 0.82480 0.928 0.072
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 2 0.5519 0.73678 0.128 0.872
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.9087 0.40579 0.676 0.324
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.87216 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 1 0.7950 0.64785 0.760 0.240
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 1 0.6148 0.78365 0.848 0.152
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.87216 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.9661 0.58014 0.392 0.608
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0376 0.87243 0.996 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1184 0.87052 0.984 0.016
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.5178 0.73516 0.116 0.884
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0672 0.87272 0.992 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.6343 0.77087 0.840 0.160
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.8555 0.71324 0.280 0.720
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1633 0.86622 0.976 0.024
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.87216 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.87216 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.2423 0.86475 0.960 0.040
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.6623 0.76271 0.828 0.172
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.1184 0.87293 0.984 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.9954 -0.12864 0.540 0.460
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.87216 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.6623 0.75231 0.828 0.172
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 1 0.6531 0.76346 0.832 0.168
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2043 0.85978 0.968 0.032
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.87216 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.9988 0.42286 0.480 0.520
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.87216 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0672 0.87300 0.992 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0672 0.87311 0.992 0.008
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.87216 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.87216 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1184 0.86851 0.984 0.016
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.0672 0.87283 0.992 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.87216 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0376 0.87243 0.996 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6247 0.77630 0.844 0.156
#> 1122039D-5785-4F70-9916-17C585453512 2 0.1633 0.69733 0.024 0.976
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.87216 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1184 0.87221 0.984 0.016
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9866 0.50243 0.432 0.568
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.2948 0.86047 0.948 0.052
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.4815 0.82761 0.896 0.104
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.1843 0.87012 0.972 0.028
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.1843 0.69955 0.028 0.972
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 2 1.0000 0.38117 0.496 0.504
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.87216 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.9996 0.33689 0.488 0.512
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.87216 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.0672 0.87226 0.992 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.87216 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.0938 0.87301 0.988 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.9710 0.57042 0.400 0.600
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.87216 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0672 0.87272 0.992 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.6343 0.74702 0.840 0.160
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.3431 0.85675 0.936 0.064
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.87216 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2236 0.86325 0.964 0.036
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1184 0.87221 0.984 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.87216 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.87216 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1414 0.86603 0.980 0.020
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.9896 0.47769 0.440 0.560
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.3733 0.72028 0.072 0.928
#> A0C429D9-0638-4873-BFB4-00056AB4719F 1 0.8955 0.47207 0.688 0.312
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.87216 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0376 0.87243 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5946 0.78880 0.856 0.144
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.87216 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.5247 0.642339 0.768 0.224 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.1267 0.766584 0.972 0.024 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.8924 0.353469 0.268 0.172 0.560
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.8939 -0.147528 0.124 0.440 0.436
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.4178 0.678189 0.828 0.172 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.7918 0.315578 0.640 0.104 0.256
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.7411 0.480654 0.668 0.256 0.076
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0475 0.765221 0.992 0.004 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.7446 0.349179 0.664 0.076 0.260
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4137 0.587625 0.096 0.032 0.872
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.7962 0.145646 0.576 0.352 0.072
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0592 0.765329 0.988 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 1 0.7458 0.445756 0.672 0.244 0.084
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.2680 0.759329 0.924 0.068 0.008
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.4966 0.668587 0.840 0.100 0.060
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.3889 0.739414 0.884 0.084 0.032
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.1267 0.766584 0.972 0.024 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 3 0.9489 0.026358 0.252 0.252 0.496
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.4002 0.690619 0.840 0.160 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 1 0.8414 -0.080754 0.528 0.380 0.092
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.1964 0.520921 0.000 0.056 0.944
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 1 0.6319 0.579648 0.732 0.228 0.040
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.763936 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.9118 0.024829 0.144 0.468 0.388
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0424 0.765912 0.992 0.008 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.9827 0.522898 0.372 0.384 0.244
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.7508 0.260637 0.416 0.040 0.544
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3769 0.737438 0.880 0.104 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2550 0.747484 0.936 0.040 0.024
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0424 0.765002 0.992 0.008 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5757 0.628542 0.792 0.056 0.152
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 1 0.8414 -0.080754 0.528 0.380 0.092
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.8676 0.322485 0.112 0.368 0.520
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1620 0.766485 0.964 0.024 0.012
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2383 0.762854 0.940 0.044 0.016
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4121 0.687365 0.832 0.168 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.4399 0.670479 0.812 0.188 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.8013 0.329325 0.636 0.112 0.252
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.763936 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.2636 0.545402 0.020 0.048 0.932
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0475 0.765221 0.992 0.004 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2448 0.751247 0.924 0.076 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 1 0.5254 0.572812 0.736 0.264 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0237 0.764339 0.996 0.004 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.3116 0.733836 0.892 0.108 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.6254 0.572105 0.116 0.108 0.776
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.1964 0.520921 0.000 0.056 0.944
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.4179 0.737886 0.876 0.072 0.052
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3112 0.753557 0.916 0.056 0.028
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.4796 0.634154 0.780 0.220 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2176 0.763044 0.948 0.032 0.020
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3896 0.719162 0.888 0.052 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.8844 0.135657 0.116 0.440 0.444
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5760 0.673810 0.796 0.140 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1170 0.760280 0.976 0.016 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0424 0.765739 0.992 0.008 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 1 0.6985 0.210176 0.592 0.384 0.024
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.4654 0.645276 0.792 0.208 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.6004 0.613325 0.780 0.064 0.156
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.4178 0.677774 0.828 0.172 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.2050 0.754150 0.952 0.028 0.020
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.7233 0.463551 0.672 0.264 0.064
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0237 0.765562 0.996 0.004 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0237 0.764719 0.996 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4569 0.665718 0.860 0.072 0.068
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.4137 0.587625 0.096 0.032 0.872
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.6388 0.513374 0.692 0.284 0.024
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.1950 0.766389 0.952 0.040 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5744 0.614573 0.800 0.072 0.128
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.763936 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.9068 -0.112461 0.136 0.444 0.420
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.2682 0.756819 0.920 0.076 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 1 0.8363 -0.185309 0.504 0.412 0.084
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.8844 0.135657 0.116 0.440 0.444
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.7726 0.454569 0.676 0.192 0.132
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.6967 0.319393 0.668 0.044 0.288
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.9601 0.179732 0.328 0.216 0.456
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.1999 0.766310 0.952 0.036 0.012
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.7447 0.546224 0.160 0.140 0.700
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.8503 0.441967 0.120 0.304 0.576
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.3038 0.735847 0.896 0.104 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 1 0.9292 -0.140228 0.516 0.284 0.200
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#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.3472 0.716032 0.904 0.056 0.040
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0424 0.765782 0.992 0.008 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4087 0.737318 0.880 0.068 0.052
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 1 0.8104 0.289306 0.616 0.280 0.104
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.4784 0.650545 0.796 0.200 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.2793 0.731385 0.928 0.044 0.028
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4137 0.587625 0.096 0.032 0.872
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.7810 0.315218 0.640 0.092 0.268
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.763936 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.8334 0.419209 0.440 0.480 0.080
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 1 0.8054 0.093818 0.568 0.356 0.076
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.1267 0.766584 0.972 0.024 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.7291 0.356952 0.356 0.040 0.604
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0475 0.766037 0.992 0.004 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1453 0.765227 0.968 0.024 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4121 0.585541 0.084 0.040 0.876
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0983 0.765564 0.980 0.016 0.004
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.6004 0.613325 0.780 0.064 0.156
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.7975 0.493308 0.204 0.140 0.656
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1482 0.763431 0.968 0.020 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0424 0.765414 0.992 0.008 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0237 0.764719 0.996 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.5404 0.573805 0.740 0.256 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.7412 0.512638 0.700 0.176 0.124
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.2301 0.764394 0.936 0.060 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.9981 0.234264 0.316 0.364 0.320
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.763936 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.7810 0.367257 0.640 0.268 0.092
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 1 0.7785 -0.081417 0.528 0.420 0.052
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1620 0.756025 0.964 0.024 0.012
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0475 0.765221 0.992 0.004 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.8454 0.228404 0.432 0.088 0.480
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.763936 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1267 0.767857 0.972 0.024 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.4750 0.639239 0.784 0.216 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.763936 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.763936 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1170 0.761159 0.976 0.016 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.3752 0.708682 0.856 0.144 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.763936 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0661 0.765922 0.988 0.004 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5222 0.654731 0.816 0.040 0.144
#> 1122039D-5785-4F70-9916-17C585453512 3 0.2636 0.545402 0.020 0.048 0.932
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0237 0.764719 0.996 0.004 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1585 0.765779 0.964 0.028 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9068 -0.112461 0.136 0.444 0.420
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.3637 0.745811 0.892 0.084 0.024
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.6978 0.347313 0.632 0.336 0.032
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.2804 0.759204 0.924 0.060 0.016
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.2846 0.546397 0.020 0.056 0.924
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.8403 0.206379 0.448 0.084 0.468
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0661 0.765712 0.988 0.008 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.9596 0.013180 0.384 0.200 0.416
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.1031 0.767696 0.976 0.024 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.4504 0.661015 0.804 0.196 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.763936 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.4399 0.665120 0.812 0.188 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.7328 0.347894 0.364 0.040 0.596
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0237 0.764317 0.996 0.004 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1267 0.766427 0.972 0.024 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.7129 0.547990 0.716 0.180 0.104
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.5858 0.589413 0.740 0.240 0.020
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0475 0.764939 0.992 0.004 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2550 0.755896 0.936 0.040 0.024
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1482 0.766265 0.968 0.020 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0237 0.764719 0.996 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.1267 0.766584 0.972 0.024 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1337 0.758897 0.972 0.012 0.016
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.8887 -0.111509 0.120 0.456 0.424
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2926 0.568352 0.040 0.036 0.924
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.7590 0.657263 0.268 0.652 0.080
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0237 0.764317 0.996 0.004 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0592 0.766235 0.988 0.012 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4551 0.673380 0.840 0.020 0.140
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0237 0.764761 0.996 0.004 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.5897 0.49995 0.704 0.224 0.024 0.048
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2019 0.74501 0.940 0.032 0.004 0.024
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.8862 0.34590 0.216 0.164 0.500 0.120
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.7013 0.81983 0.024 0.104 0.256 0.616
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.4220 0.51839 0.748 0.248 0.000 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.7051 0.27891 0.612 0.088 0.268 0.032
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.6724 0.21986 0.588 0.332 0.052 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0376 0.75081 0.992 0.004 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6748 0.29076 0.644 0.064 0.252 0.040
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2593 0.39494 0.080 0.000 0.904 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.7804 -0.41913 0.468 0.396 0.048 0.088
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0524 0.75097 0.988 0.008 0.004 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 1 0.7342 0.05800 0.584 0.292 0.068 0.056
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.3283 0.71097 0.872 0.104 0.020 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5122 0.63238 0.796 0.112 0.048 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.3827 0.70486 0.860 0.080 0.048 0.012
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.2019 0.74501 0.940 0.032 0.004 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 3 0.9482 -0.02893 0.188 0.220 0.420 0.172
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.4123 0.56877 0.772 0.220 0.000 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.8491 0.58751 0.396 0.404 0.060 0.140
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.3972 0.04260 0.000 0.008 0.788 0.204
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 1 0.5736 0.28556 0.640 0.324 0.016 0.020
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 4 0.8117 0.75002 0.048 0.196 0.212 0.544
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0336 0.75157 0.992 0.008 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.9665 0.45604 0.248 0.376 0.168 0.208
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5970 0.32694 0.388 0.024 0.576 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4475 0.66674 0.824 0.096 0.012 0.068
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2418 0.73268 0.928 0.032 0.024 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0376 0.75043 0.992 0.004 0.004 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5044 0.59844 0.780 0.044 0.156 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.8491 0.58751 0.396 0.404 0.060 0.140
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.7581 0.69764 0.064 0.060 0.352 0.524
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1707 0.74874 0.952 0.024 0.020 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2456 0.74221 0.924 0.040 0.028 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4635 0.49052 0.720 0.268 0.000 0.012
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.4908 0.43681 0.692 0.292 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.7214 0.28558 0.604 0.088 0.268 0.040
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.3997 0.15762 0.012 0.008 0.816 0.164
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0376 0.75081 0.992 0.004 0.004 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2921 0.68715 0.860 0.140 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 1 0.5835 0.13644 0.588 0.372 0.000 0.040
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0188 0.75049 0.996 0.004 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.3725 0.63592 0.812 0.180 0.000 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.5015 0.37849 0.088 0.076 0.804 0.032
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.3972 0.04260 0.000 0.008 0.788 0.204
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.4573 0.68543 0.832 0.072 0.048 0.048
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.2936 0.72834 0.900 0.056 0.040 0.004
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.4744 0.43634 0.704 0.284 0.000 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2165 0.74698 0.936 0.032 0.024 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3587 0.70047 0.876 0.052 0.056 0.016
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.6788 0.81647 0.016 0.104 0.252 0.628
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5576 0.59735 0.756 0.140 0.084 0.020
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1139 0.74689 0.972 0.012 0.008 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0469 0.75124 0.988 0.012 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.5770 0.48904 0.432 0.544 0.012 0.012
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.5173 0.35654 0.660 0.320 0.000 0.020
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5797 0.53841 0.740 0.056 0.168 0.036
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.4313 0.49733 0.736 0.260 0.000 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1975 0.73940 0.944 0.028 0.016 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.7375 -0.00923 0.556 0.324 0.040 0.080
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0188 0.75096 0.996 0.004 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0188 0.75018 0.996 0.000 0.004 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4277 0.65229 0.844 0.076 0.052 0.028
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.2593 0.39494 0.080 0.000 0.904 0.016
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.6384 0.18298 0.612 0.320 0.016 0.052
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2099 0.74648 0.936 0.044 0.012 0.008
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5202 0.59626 0.788 0.060 0.120 0.032
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.7197 0.81560 0.036 0.104 0.244 0.616
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.3043 0.71198 0.876 0.112 0.008 0.004
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.7129 0.65578 0.336 0.564 0.056 0.044
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.6788 0.81647 0.016 0.104 0.252 0.628
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.7527 0.27005 0.620 0.196 0.124 0.060
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.6462 0.31384 0.644 0.044 0.276 0.036
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.9050 0.33472 0.288 0.204 0.424 0.084
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.2297 0.74367 0.928 0.044 0.024 0.004
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.6789 0.40396 0.128 0.120 0.692 0.060
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.8425 -0.12441 0.076 0.128 0.496 0.300
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.3494 0.64768 0.824 0.172 0.000 0.004
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 1 0.9036 -0.50433 0.424 0.320 0.144 0.112
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0188 0.75023 0.996 0.004 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.7587 0.17040 0.596 0.084 0.248 0.072
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1302 0.74379 0.956 0.044 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 1 0.5178 0.11657 0.600 0.392 0.004 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.5015 0.37703 0.088 0.076 0.804 0.032
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#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.4830 0.14877 0.608 0.392 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.2123 0.74499 0.936 0.032 0.004 0.028
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.8722 0.50831 0.304 0.448 0.184 0.064
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.6951 0.57556 0.400 0.520 0.036 0.044
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4840 0.62805 0.812 0.100 0.056 0.032
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.4697 0.27407 0.644 0.356 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.5181 0.62862 0.792 0.092 0.088 0.028
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.8629 0.37651 0.232 0.132 0.520 0.116
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 1 0.4697 0.27407 0.644 0.356 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.3365 0.70241 0.888 0.056 0.024 0.032
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0376 0.75133 0.992 0.004 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4357 0.69022 0.844 0.052 0.056 0.048
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 1 0.8024 -0.25357 0.512 0.328 0.084 0.076
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.4621 0.44076 0.708 0.284 0.000 0.008
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.2627 0.71987 0.920 0.036 0.020 0.024
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2593 0.39494 0.080 0.000 0.904 0.016
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.7141 0.29519 0.616 0.088 0.256 0.040
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.7215 0.61002 0.272 0.604 0.048 0.076
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.7228 0.59171 0.400 0.504 0.056 0.040
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2019 0.74501 0.940 0.032 0.004 0.024
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.5660 0.40589 0.336 0.024 0.632 0.008
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0336 0.75137 0.992 0.000 0.008 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1739 0.75048 0.952 0.024 0.016 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.2707 0.38325 0.068 0.008 0.908 0.016
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1114 0.75046 0.972 0.008 0.016 0.004
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.5721 0.54489 0.744 0.052 0.168 0.036
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.7974 0.37916 0.168 0.124 0.600 0.108
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1484 0.74758 0.960 0.020 0.016 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0336 0.75119 0.992 0.008 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0188 0.75018 0.996 0.000 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.4855 0.11797 0.600 0.400 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.7509 0.26910 0.624 0.200 0.104 0.072
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.2528 0.73700 0.908 0.080 0.004 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.9186 -0.03920 0.180 0.428 0.280 0.112
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.7600 -0.11598 0.544 0.324 0.076 0.056
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.6488 0.61988 0.372 0.568 0.032 0.028
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1486 0.74395 0.960 0.024 0.008 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0376 0.75081 0.992 0.004 0.004 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.7263 0.30182 0.404 0.068 0.496 0.032
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1191 0.75267 0.968 0.024 0.004 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.5404 0.31951 0.644 0.328 0.000 0.028
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0967 0.74897 0.976 0.016 0.004 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.3852 0.60723 0.800 0.192 0.000 0.008
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0469 0.75120 0.988 0.000 0.012 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4380 0.61688 0.800 0.032 0.164 0.004
#> 1122039D-5785-4F70-9916-17C585453512 3 0.3997 0.15762 0.012 0.008 0.816 0.164
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0188 0.75018 0.996 0.000 0.004 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1811 0.74703 0.948 0.028 0.020 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.7197 0.81560 0.036 0.104 0.244 0.616
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.3739 0.70632 0.868 0.076 0.024 0.032
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.6103 0.36160 0.480 0.484 0.024 0.012
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.3299 0.72332 0.888 0.056 0.012 0.044
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4241 0.16506 0.012 0.016 0.808 0.164
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.7093 0.25526 0.428 0.060 0.484 0.028
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0524 0.75109 0.988 0.004 0.008 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.9016 0.18979 0.344 0.196 0.384 0.076
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0921 0.75046 0.972 0.028 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.5157 0.42080 0.688 0.284 0.000 0.028
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.74964 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.4516 0.49930 0.736 0.252 0.000 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.5857 0.40586 0.340 0.032 0.620 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0188 0.74964 0.996 0.004 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1369 0.75046 0.964 0.016 0.016 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.6871 0.45222 0.672 0.172 0.112 0.044
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.6057 0.33368 0.648 0.288 0.008 0.056
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0336 0.75046 0.992 0.000 0.008 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2521 0.74036 0.924 0.032 0.028 0.016
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1707 0.74776 0.952 0.024 0.020 0.004
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0188 0.75018 0.996 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.2019 0.74501 0.940 0.032 0.004 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1229 0.74533 0.968 0.020 0.008 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.7373 0.75442 0.020 0.144 0.256 0.580
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1707 0.30305 0.024 0.004 0.952 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.7090 0.14168 0.112 0.600 0.020 0.268
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0188 0.74964 0.996 0.004 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0657 0.75226 0.984 0.012 0.004 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3983 0.64285 0.828 0.020 0.144 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0188 0.75023 0.996 0.004 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.6163 0.33682 0.624 0.236 0.024 0.004 0.112
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2596 0.71815 0.908 0.032 0.004 0.036 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.8525 0.40994 0.164 0.116 0.488 0.064 0.168
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.2387 0.80694 0.004 0.040 0.048 0.908 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.5191 0.25349 0.624 0.324 0.000 0.008 0.044
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.6657 0.22164 0.552 0.032 0.272 0.000 0.144
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.6927 -0.10204 0.484 0.348 0.044 0.000 0.124
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0451 0.73114 0.988 0.000 0.008 0.000 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6503 0.29144 0.620 0.076 0.244 0.032 0.028
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1809 0.49711 0.060 0.000 0.928 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.7737 0.47147 0.360 0.428 0.032 0.040 0.140
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0486 0.73079 0.988 0.004 0.004 0.000 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 1 0.7308 -0.28949 0.468 0.372 0.056 0.024 0.080
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4127 0.63517 0.792 0.156 0.024 0.000 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5158 0.59588 0.756 0.068 0.036 0.012 0.128
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4291 0.65172 0.808 0.092 0.056 0.000 0.044
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.2596 0.71815 0.908 0.032 0.004 0.036 0.020
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 3 0.9328 -0.10271 0.140 0.240 0.372 0.108 0.140
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.5250 0.34529 0.656 0.280 0.000 0.016 0.048
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.8219 0.43799 0.280 0.436 0.040 0.056 0.188
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.5051 0.09402 0.000 0.000 0.664 0.264 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 1 0.5886 -0.13089 0.520 0.412 0.004 0.036 0.028
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0162 0.72915 0.996 0.000 0.000 0.000 0.004
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 4 0.5510 0.71566 0.024 0.132 0.056 0.740 0.048
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0693 0.73266 0.980 0.008 0.000 0.000 0.012
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.9212 0.13511 0.180 0.416 0.128 0.128 0.148
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5406 0.36691 0.348 0.008 0.592 0.000 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.5010 0.59705 0.764 0.116 0.008 0.080 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2131 0.71647 0.920 0.008 0.016 0.000 0.056
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0613 0.73194 0.984 0.004 0.004 0.000 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.4887 0.58258 0.756 0.024 0.160 0.008 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.8219 0.43799 0.280 0.436 0.040 0.056 0.188
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4866 0.73152 0.048 0.016 0.144 0.768 0.024
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2418 0.72059 0.912 0.044 0.024 0.000 0.020
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2617 0.71976 0.904 0.036 0.032 0.000 0.028
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.5733 0.28031 0.616 0.276 0.000 0.008 0.100
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5993 0.17594 0.576 0.312 0.000 0.012 0.100
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6729 0.25288 0.556 0.028 0.264 0.004 0.148
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0404 0.73046 0.988 0.000 0.000 0.000 0.012
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4712 0.21819 0.004 0.000 0.720 0.216 0.060
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0451 0.73114 0.988 0.000 0.008 0.000 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3936 0.61435 0.800 0.144 0.000 0.004 0.052
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 1 0.6528 -0.23765 0.444 0.408 0.000 0.012 0.136
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0290 0.73042 0.992 0.000 0.000 0.000 0.008
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.4555 0.52894 0.740 0.196 0.000 0.004 0.060
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4506 0.49271 0.056 0.068 0.812 0.016 0.048
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.5051 0.09402 0.000 0.000 0.664 0.264 0.072
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5018 0.63409 0.780 0.088 0.048 0.064 0.020
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3569 0.68762 0.852 0.072 0.040 0.000 0.036
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.5552 0.13466 0.588 0.340 0.000 0.008 0.064
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2772 0.72075 0.896 0.044 0.028 0.000 0.032
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3538 0.67548 0.848 0.016 0.056 0.000 0.080
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.1981 0.80799 0.000 0.028 0.048 0.924 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5926 0.51281 0.700 0.120 0.092 0.004 0.084
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0992 0.72957 0.968 0.000 0.008 0.000 0.024
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0771 0.73211 0.976 0.020 0.000 0.000 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.4910 0.48053 0.328 0.640 0.004 0.008 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.6279 0.00252 0.520 0.352 0.000 0.012 0.116
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5705 0.51176 0.712 0.052 0.172 0.036 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.5334 0.21477 0.612 0.328 0.000 0.008 0.052
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1757 0.72173 0.936 0.004 0.012 0.000 0.048
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.7955 -0.28724 0.444 0.328 0.024 0.112 0.092
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0613 0.73259 0.984 0.008 0.004 0.000 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0162 0.72974 0.996 0.000 0.004 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4054 0.63759 0.812 0.028 0.040 0.000 0.120
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1809 0.49711 0.060 0.000 0.928 0.012 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.6577 -0.14407 0.520 0.344 0.012 0.012 0.112
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2568 0.71850 0.904 0.048 0.016 0.000 0.032
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4519 0.59124 0.764 0.004 0.120 0.000 0.112
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
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#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.5414 0.46206 0.696 0.060 0.216 0.012 0.016
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.4138 0.20058 0.616 0.384 0.000 0.000 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 1 0.5302 0.23633 0.620 0.320 0.000 0.008 0.052
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.5614 0.49434 0.396 0.552 0.012 0.024 0.016
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.3766 0.47720 0.728 0.268 0.000 0.000 0.004
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 1 0.7007 -0.16252 0.516 0.348 0.056 0.040 0.040
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0404 0.73046 0.988 0.000 0.000 0.000 0.012
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.2972 0.68490 0.872 0.084 0.000 0.004 0.040
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.3845 0.62541 0.812 0.124 0.000 0.004 0.060
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.5244 0.48663 0.060 0.072 0.764 0.016 0.088
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 1 0.7461 -0.29721 0.440 0.384 0.020 0.060 0.096
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 1 0.5758 0.22932 0.612 0.304 0.016 0.004 0.064
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 4 0.8732 0.18659 0.076 0.264 0.140 0.428 0.092
#> 80936433-AA91-4219-98F1-706C36298060 3 0.5821 0.11908 0.000 0.024 0.652 0.220 0.104
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.4566 0.61687 0.796 0.012 0.084 0.020 0.088
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.3609 0.66072 0.832 0.128 0.012 0.004 0.024
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0290 0.73120 0.992 0.000 0.000 0.000 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0404 0.73120 0.988 0.000 0.000 0.000 0.012
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 4 0.1981 0.80799 0.000 0.028 0.048 0.924 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0579 0.73237 0.984 0.000 0.008 0.000 0.008
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0579 0.73090 0.984 0.008 0.000 0.000 0.008
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.5283 0.40364 0.672 0.240 0.000 0.008 0.080
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.1243 0.73389 0.960 0.028 0.004 0.000 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.1597 0.48839 0.048 0.000 0.940 0.012 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.5749 0.44025 0.680 0.060 0.216 0.012 0.032
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.2596 0.71815 0.908 0.032 0.004 0.036 0.020
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.1216 0.73402 0.960 0.020 0.000 0.000 0.020
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0404 0.73046 0.988 0.000 0.000 0.000 0.012
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.5014 0.44679 0.432 0.540 0.004 0.000 0.024
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.1443 0.72993 0.948 0.044 0.004 0.000 0.004
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.3214 0.67532 0.856 0.020 0.112 0.004 0.008
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.5113 0.58122 0.748 0.044 0.088 0.000 0.120
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.1443 0.72993 0.948 0.044 0.004 0.000 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1777 0.73051 0.944 0.020 0.020 0.004 0.012
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.2186 0.72536 0.924 0.044 0.012 0.004 0.016
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.2919 0.67418 0.868 0.004 0.024 0.000 0.104
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.4305 -0.21608 0.512 0.488 0.000 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.2473 0.72224 0.912 0.040 0.004 0.032 0.012
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.8142 0.18541 0.232 0.488 0.168 0.048 0.064
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.6052 0.47829 0.316 0.596 0.012 0.040 0.036
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4439 0.61174 0.784 0.036 0.040 0.000 0.140
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.4273 -0.06132 0.552 0.448 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.4923 0.59994 0.764 0.044 0.088 0.000 0.104
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.8225 0.44192 0.180 0.068 0.500 0.060 0.192
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0404 0.73046 0.988 0.000 0.000 0.000 0.012
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 1 0.4273 -0.06132 0.552 0.448 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.3375 0.68520 0.864 0.012 0.024 0.016 0.084
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0451 0.73203 0.988 0.000 0.004 0.000 0.008
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4756 0.65105 0.800 0.068 0.060 0.048 0.024
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 1 0.7917 -0.46261 0.400 0.392 0.076 0.036 0.096
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.5536 0.10787 0.580 0.352 0.000 0.008 0.060
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.2332 0.70526 0.904 0.004 0.016 0.000 0.076
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.1809 0.49711 0.060 0.000 0.928 0.012 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6803 0.26393 0.568 0.032 0.248 0.008 0.144
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0162 0.72915 0.996 0.000 0.000 0.000 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.6499 0.18784 0.196 0.644 0.024 0.040 0.096
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.6340 0.48478 0.296 0.596 0.052 0.020 0.036
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2596 0.71815 0.908 0.032 0.004 0.036 0.020
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.5159 0.42233 0.300 0.004 0.640 0.000 0.056
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0740 0.73212 0.980 0.004 0.008 0.000 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1891 0.73086 0.936 0.016 0.016 0.000 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1757 0.48922 0.048 0.004 0.936 0.012 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1503 0.73010 0.952 0.020 0.020 0.000 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.5639 0.51846 0.716 0.048 0.172 0.036 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.7575 0.48215 0.124 0.072 0.588 0.060 0.156
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1748 0.73059 0.944 0.008 0.016 0.004 0.028
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0290 0.73120 0.992 0.000 0.000 0.000 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0162 0.72974 0.996 0.000 0.004 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.4307 -0.24451 0.504 0.496 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.7387 0.10698 0.560 0.240 0.080 0.092 0.028
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3406 0.69777 0.856 0.084 0.020 0.000 0.040
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 5 0.8854 0.02942 0.100 0.288 0.276 0.036 0.300
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0162 0.72915 0.996 0.000 0.000 0.000 0.004
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.7551 -0.38920 0.428 0.392 0.064 0.024 0.092
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.5623 0.44370 0.284 0.644 0.020 0.016 0.036
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1591 0.72508 0.940 0.004 0.004 0.000 0.052
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0451 0.73114 0.988 0.000 0.008 0.000 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.6387 0.35610 0.352 0.008 0.500 0.000 0.140
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1364 0.73142 0.952 0.036 0.012 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.6360 -0.03570 0.508 0.356 0.000 0.012 0.124
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0566 0.73087 0.984 0.004 0.000 0.000 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0566 0.73087 0.984 0.004 0.000 0.000 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1124 0.72995 0.960 0.000 0.004 0.000 0.036
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.4865 0.38737 0.672 0.280 0.000 0.004 0.044
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0854 0.73221 0.976 0.004 0.012 0.000 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4100 0.60246 0.784 0.028 0.172 0.000 0.016
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4712 0.21819 0.004 0.000 0.720 0.216 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0451 0.73167 0.988 0.008 0.004 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2492 0.71800 0.908 0.048 0.024 0.000 0.020
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.2443 0.80218 0.008 0.036 0.040 0.912 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.4138 0.65530 0.824 0.100 0.020 0.020 0.036
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5514 0.49210 0.396 0.556 0.024 0.008 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.3835 0.68922 0.848 0.064 0.016 0.048 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4946 0.22470 0.004 0.000 0.704 0.216 0.076
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.6002 0.29734 0.392 0.000 0.492 0.000 0.116
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0451 0.73104 0.988 0.000 0.008 0.000 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.8550 0.25756 0.288 0.128 0.384 0.020 0.180
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.1205 0.73032 0.956 0.040 0.000 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.6208 0.13953 0.568 0.312 0.000 0.024 0.096
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0290 0.72962 0.992 0.000 0.000 0.000 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.5287 0.22004 0.612 0.332 0.000 0.008 0.048
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.5295 0.42002 0.304 0.004 0.628 0.000 0.064
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0162 0.72945 0.996 0.000 0.000 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.2072 0.72548 0.928 0.036 0.020 0.000 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.6956 0.34442 0.604 0.120 0.112 0.004 0.160
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.7148 0.01435 0.536 0.276 0.004 0.088 0.096
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0290 0.73042 0.992 0.000 0.008 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2745 0.72000 0.896 0.024 0.028 0.000 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.2291 0.71964 0.916 0.048 0.024 0.000 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0324 0.73070 0.992 0.000 0.004 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.2596 0.71815 0.908 0.032 0.004 0.036 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1412 0.72615 0.952 0.004 0.008 0.000 0.036
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.5128 0.70596 0.004 0.084 0.148 0.740 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1200 0.43397 0.012 0.000 0.964 0.016 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.7024 -0.52486 0.068 0.436 0.012 0.060 0.424
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0162 0.72945 0.996 0.000 0.000 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0932 0.73309 0.972 0.020 0.004 0.000 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3763 0.62881 0.812 0.024 0.152 0.004 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0451 0.73072 0.988 0.008 0.000 0.000 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.6865 0.14969 0.544 0.124 0.024 0.000 0.216 0.092
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3138 0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.7755 0.40260 0.124 0.296 0.440 0.020 0.040 0.080
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1036 0.78893 0.000 0.024 0.000 0.964 0.008 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.5489 -0.18661 0.496 0.100 0.000 0.000 0.396 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.6636 0.15701 0.512 0.148 0.280 0.000 0.020 0.040
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.7014 -0.21036 0.432 0.340 0.044 0.000 0.156 0.028
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0603 0.73378 0.980 0.000 0.004 0.000 0.016 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6583 0.27814 0.584 0.104 0.220 0.008 0.060 0.024
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1616 0.49382 0.048 0.000 0.932 0.000 0.000 0.020
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3964 0.56830 0.228 0.012 0.004 0.004 0.740 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0653 0.73361 0.980 0.004 0.004 0.000 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.5072 0.47218 0.340 0.040 0.016 0.000 0.596 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4015 0.55340 0.724 0.012 0.016 0.000 0.244 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5119 0.60717 0.740 0.132 0.032 0.012 0.052 0.032
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4540 0.63627 0.772 0.112 0.040 0.000 0.056 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.3138 0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.8007 -0.16576 0.100 0.060 0.308 0.036 0.424 0.072
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.5853 0.00707 0.532 0.108 0.000 0.012 0.336 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.3733 0.55752 0.156 0.004 0.012 0.004 0.796 0.028
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.6207 0.08463 0.000 0.040 0.580 0.240 0.016 0.124
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 1 0.6714 -0.40957 0.412 0.184 0.000 0.036 0.360 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0291 0.73234 0.992 0.004 0.000 0.000 0.004 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 4 0.4685 0.69239 0.012 0.088 0.012 0.776 0.060 0.052
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0881 0.73633 0.972 0.008 0.000 0.000 0.012 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.6726 0.15970 0.092 0.112 0.064 0.060 0.640 0.032
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#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0767 0.73416 0.976 0.004 0.000 0.000 0.012 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0767 0.73416 0.976 0.004 0.000 0.000 0.012 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1198 0.73578 0.960 0.020 0.004 0.000 0.004 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.5510 0.18378 0.584 0.104 0.000 0.000 0.292 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0837 0.73596 0.972 0.004 0.000 0.000 0.020 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0912 0.73615 0.972 0.008 0.012 0.000 0.004 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4406 0.60643 0.760 0.032 0.152 0.000 0.048 0.008
#> 1122039D-5785-4F70-9916-17C585453512 3 0.5279 0.22319 0.000 0.040 0.676 0.204 0.008 0.072
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0692 0.73538 0.976 0.000 0.004 0.000 0.020 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2458 0.71570 0.888 0.008 0.016 0.000 0.084 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.1053 0.78683 0.004 0.020 0.000 0.964 0.012 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.4001 0.61907 0.776 0.032 0.004 0.004 0.168 0.016
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7003 0.41704 0.340 0.376 0.024 0.004 0.240 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4124 0.68119 0.820 0.044 0.012 0.052 0.052 0.020
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.5608 0.22443 0.000 0.056 0.656 0.204 0.012 0.072
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.6018 0.28379 0.376 0.088 0.496 0.000 0.008 0.032
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0653 0.73413 0.980 0.000 0.004 0.000 0.012 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.7707 0.21271 0.244 0.316 0.336 0.000 0.044 0.060
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.1334 0.73463 0.948 0.032 0.000 0.000 0.020 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.7300 -0.06954 0.460 0.208 0.000 0.016 0.220 0.096
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0551 0.73350 0.984 0.004 0.000 0.000 0.008 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.5517 -0.22096 0.488 0.092 0.000 0.000 0.408 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4993 0.42962 0.288 0.048 0.640 0.000 0.008 0.016
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0363 0.73246 0.988 0.000 0.000 0.000 0.012 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.2144 0.72401 0.908 0.008 0.012 0.000 0.068 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.6959 0.27518 0.544 0.228 0.104 0.000 0.072 0.052
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 1 0.7863 -0.20329 0.436 0.184 0.000 0.092 0.220 0.068
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0748 0.73654 0.976 0.000 0.004 0.000 0.016 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3249 0.71758 0.864 0.040 0.028 0.000 0.044 0.024
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.2370 0.71888 0.896 0.008 0.012 0.000 0.076 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0665 0.73464 0.980 0.008 0.004 0.000 0.008 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.3138 0.70294 0.864 0.012 0.000 0.040 0.064 0.020
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1382 0.73161 0.948 0.036 0.008 0.000 0.000 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.4923 0.67587 0.000 0.120 0.072 0.744 0.040 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1198 0.44347 0.000 0.012 0.960 0.004 0.004 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F 6 0.6430 0.53942 0.016 0.180 0.004 0.004 0.388 0.408
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0363 0.73246 0.988 0.000 0.000 0.000 0.012 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1293 0.73753 0.956 0.016 0.004 0.000 0.020 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3984 0.63351 0.796 0.028 0.136 0.004 0.028 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0405 0.73439 0.988 0.004 0.000 0.000 0.008 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.359 0.770 0.851 0.4681 0.517 0.517
#> 3 3 0.797 0.845 0.932 0.3239 0.781 0.612
#> 4 4 0.647 0.683 0.816 0.1151 0.910 0.777
#> 5 5 0.608 0.620 0.774 0.0709 0.951 0.853
#> 6 6 0.618 0.505 0.697 0.0569 0.909 0.713
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5737 0.8711 0.136 0.864
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.6623 0.7168 0.828 0.172
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.6343 0.7382 0.160 0.840
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.5408 0.8688 0.124 0.876
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.9044 0.6139 0.320 0.680
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.5737 0.7700 0.864 0.136
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.5842 0.7686 0.860 0.140
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.8863 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.9710 0.5669 0.400 0.600
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.9954 0.1438 0.460 0.540
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.5737 0.8711 0.136 0.864
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.8863 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.5737 0.8711 0.136 0.864
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0000 0.8863 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.4815 0.8030 0.896 0.104
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.8863 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.8327 0.5809 0.736 0.264
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.8028 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5737 0.8711 0.136 0.864
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.5737 0.8711 0.136 0.864
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.2043 0.8029 0.032 0.968
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.5737 0.8711 0.136 0.864
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8863 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5519 0.8702 0.128 0.872
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.8863 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.5519 0.8702 0.128 0.872
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.5842 0.7686 0.860 0.140
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.8144 0.6009 0.748 0.252
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.8863 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.8863 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0000 0.8863 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.5737 0.8711 0.136 0.864
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.8028 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.8863 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.8863 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.8327 0.5809 0.736 0.264
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.5737 0.8711 0.136 0.864
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.5178 0.7891 0.884 0.116
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.8863 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.4161 0.7887 0.084 0.916
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.8863 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.8863 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.5737 0.8711 0.136 0.864
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8863 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0376 0.8836 0.996 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.9248 0.4786 0.340 0.660
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.8028 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5178 0.7824 0.884 0.116
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.8863 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.5737 0.8711 0.136 0.864
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.8863 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.8863 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.4815 0.8604 0.104 0.896
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.8863 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.8863 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.8863 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.5519 0.8702 0.128 0.872
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.9815 0.2193 0.580 0.420
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.7950 0.5463 0.760 0.240
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.5737 0.8711 0.136 0.864
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.8863 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.5737 0.8711 0.136 0.864
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.8863 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.8863 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4939 0.7967 0.892 0.108
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.8555 0.5913 0.280 0.720
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5737 0.8711 0.136 0.864
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.8863 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4939 0.7967 0.892 0.108
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.8863 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.5519 0.8702 0.128 0.872
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.6712 0.7067 0.824 0.176
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.5519 0.8702 0.128 0.872
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.4815 0.8604 0.104 0.896
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.9710 0.0518 0.600 0.400
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.5059 0.7743 0.112 0.888
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.9552 0.3958 0.376 0.624
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.0000 0.8863 1.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.9286 0.4700 0.344 0.656
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.2236 0.8025 0.036 0.964
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.1633 0.8681 0.976 0.024
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.5737 0.8711 0.136 0.864
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.8863 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.5737 0.8711 0.136 0.864
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.8863 1.000 0.000
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#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.8863 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9775 0.2441 0.588 0.412
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.8863 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.8863 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.8863 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 2 0.5294 0.7692 0.120 0.880
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.8863 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.8863 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.5519 0.8702 0.128 0.872
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.9323 0.4145 0.652 0.348
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5737 0.8711 0.136 0.864
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4562 0.8016 0.904 0.096
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.6623 0.7273 0.172 0.828
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.5737 0.7700 0.864 0.136
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.8863 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.9358 0.4532 0.352 0.648
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.8863 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5737 0.8711 0.136 0.864
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.8863 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.9963 0.0634 0.536 0.464
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.5842 0.7686 0.860 0.140
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.8863 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.8863 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5737 0.7700 0.864 0.136
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.5737 0.8711 0.136 0.864
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.8863 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4690 0.8038 0.900 0.100
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.8863 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.8863 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.9286 0.4237 0.656 0.344
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.8863 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5178 0.8656 0.116 0.884
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.6623 0.7273 0.172 0.828
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.5519 0.8702 0.128 0.872
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.8863 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.8863 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.8863 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.8863 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0237 0.9470 0.000 0.996 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.5012 0.7046 0.788 0.204 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1491 0.9087 0.016 0.016 0.968
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0592 0.9467 0.000 0.988 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0424 0.9472 0.000 0.992 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.6045 0.3811 0.620 0.000 0.380
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.6026 0.3913 0.624 0.000 0.376
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9166 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.9491 -0.1706 0.420 0.184 0.396
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1525 0.9110 0.032 0.004 0.964
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0424 0.9472 0.000 0.992 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.9166 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0424 0.9472 0.000 0.992 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0237 0.9139 0.996 0.000 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.4733 0.7260 0.800 0.004 0.196
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.9166 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.6661 0.3299 0.588 0.400 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0892 0.9418 0.000 0.980 0.020
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0592 0.9460 0.000 0.988 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0424 0.9472 0.000 0.992 0.008
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.1031 0.8965 0.000 0.024 0.976
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0424 0.9472 0.000 0.992 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9166 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0424 0.9469 0.000 0.992 0.008
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9166 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0592 0.9462 0.000 0.988 0.012
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3340 0.8420 0.120 0.000 0.880
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6686 0.3952 0.612 0.372 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.9166 1.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9166 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5560 0.5331 0.700 0.000 0.300
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0424 0.9472 0.000 0.992 0.008
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0892 0.9441 0.000 0.980 0.020
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9166 1.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.9166 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.7063 0.1074 0.516 0.464 0.020
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.1031 0.9421 0.000 0.976 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4346 0.7382 0.816 0.000 0.184
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9166 1.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.1182 0.9064 0.012 0.012 0.976
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.9166 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0747 0.9062 0.984 0.000 0.016
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1031 0.9421 0.000 0.976 0.024
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9166 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.1170 0.9010 0.976 0.008 0.016
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1399 0.9119 0.028 0.004 0.968
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.1031 0.8965 0.000 0.024 0.976
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5269 0.7020 0.784 0.200 0.016
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.9166 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0424 0.9472 0.000 0.992 0.008
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9166 1.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.9166 1.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0592 0.9467 0.000 0.988 0.012
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.9166 1.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9166 1.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.9166 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0424 0.9469 0.000 0.992 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1267 0.9407 0.004 0.972 0.024
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5070 0.6641 0.772 0.004 0.224
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0424 0.9472 0.000 0.992 0.008
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.9166 1.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0892 0.9430 0.000 0.980 0.020
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9166 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.9166 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4002 0.7799 0.840 0.000 0.160
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1399 0.9119 0.028 0.004 0.968
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0424 0.9470 0.000 0.992 0.008
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.9166 1.000 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.9166 1.000 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.9166 1.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0592 0.9467 0.000 0.988 0.012
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.4912 0.7069 0.796 0.196 0.008
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0424 0.9469 0.000 0.992 0.008
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.3551 0.8324 0.000 0.868 0.132
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.6330 0.2893 0.600 0.004 0.396
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.1182 0.9065 0.012 0.012 0.976
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1525 0.9110 0.032 0.004 0.964
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.2590 0.8535 0.924 0.072 0.004
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1399 0.9119 0.028 0.004 0.968
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1163 0.8963 0.000 0.028 0.972
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.1315 0.8976 0.972 0.008 0.020
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0892 0.9421 0.000 0.980 0.020
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.9166 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.4346 0.7550 0.000 0.816 0.184
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.9166 1.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0424 0.9469 0.000 0.992 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9166 1.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1399 0.9119 0.028 0.004 0.968
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.9166 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0424 0.9469 0.000 0.992 0.008
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.9166 1.000 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.0000 0.9166 1.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.7159 0.1439 0.448 0.528 0.024
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0424 0.9472 0.000 0.992 0.008
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.9166 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0424 0.9472 0.000 0.992 0.008
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0892 0.9430 0.000 0.980 0.020
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0424 0.9472 0.000 0.992 0.008
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.4963 0.7337 0.200 0.008 0.792
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0424 0.9469 0.000 0.992 0.008
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.9166 1.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.9166 1.000 0.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.0829 0.9054 0.984 0.012 0.004
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.2625 0.8834 0.000 0.916 0.084
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.4291 0.7434 0.820 0.000 0.180
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.1399 0.9119 0.028 0.004 0.968
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.5285 0.6866 0.244 0.004 0.752
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0000 0.9166 1.000 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0424 0.9469 0.000 0.992 0.008
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.9166 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.0661 0.9459 0.004 0.988 0.008
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.1267 0.9407 0.004 0.972 0.024
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0424 0.9469 0.000 0.992 0.008
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.0000 0.9166 1.000 0.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.2773 0.8996 0.048 0.928 0.024
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0424 0.9472 0.000 0.992 0.008
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0000 0.9166 1.000 0.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0424 0.9469 0.000 0.992 0.008
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.6521 0.0821 0.492 0.004 0.504
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.9166 1.000 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0000 0.9166 1.000 0.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.9166 1.000 0.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0424 0.9469 0.000 0.992 0.008
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.1411 0.9092 0.036 0.000 0.964
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0424 0.9470 0.000 0.992 0.008
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.0000 0.9166 1.000 0.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.0237 0.9138 0.996 0.000 0.004
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.0747 0.9062 0.984 0.000 0.016
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.9166 1.000 0.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 3 0.1170 0.9090 0.016 0.008 0.976
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.0000 0.9166 1.000 0.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0424 0.9472 0.000 0.992 0.008
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.4883 0.6887 0.788 0.004 0.208
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.0000 0.9166 1.000 0.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.0000 0.9166 1.000 0.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.1337 0.9089 0.016 0.012 0.972
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#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9166 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.9166 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9166 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9166 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.6617 0.3444 0.388 0.600 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9166 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.3551 0.8285 0.000 0.868 0.132
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1337 0.9089 0.016 0.012 0.972
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0424 0.9472 0.000 0.992 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9166 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9166 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.9166 1.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9166 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4072 0.43178 0.000 0.748 0.000 0.252
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.7180 0.27129 0.504 0.148 0.000 0.348
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0817 0.85124 0.000 0.000 0.976 0.024
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5511 0.42311 0.000 0.352 0.028 0.620
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.4855 0.67400 0.000 0.400 0.000 0.600
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.6201 0.33339 0.564 0.000 0.376 0.060
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.8397 -0.01309 0.416 0.116 0.400 0.068
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0188 0.86761 0.996 0.000 0.000 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.8887 -0.01449 0.400 0.132 0.368 0.100
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0376 0.85378 0.004 0.000 0.992 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.4382 0.76647 0.000 0.296 0.000 0.704
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0707 0.86460 0.980 0.000 0.000 0.020
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 4 0.4406 0.76535 0.000 0.300 0.000 0.700
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.1474 0.85864 0.948 0.000 0.000 0.052
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6980 0.62056 0.672 0.064 0.168 0.096
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.1635 0.85744 0.948 0.008 0.000 0.044
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.7812 0.05525 0.348 0.256 0.000 0.396
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 4 0.4776 0.75736 0.000 0.272 0.016 0.712
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.4955 0.47496 0.000 0.444 0.000 0.556
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 4 0.4535 0.76739 0.000 0.292 0.004 0.704
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.2469 0.82097 0.000 0.000 0.892 0.108
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.4996 -0.42850 0.000 0.516 0.000 0.484
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5167 -0.38959 0.000 0.508 0.004 0.488
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 4 0.4647 0.76539 0.000 0.288 0.008 0.704
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.1978 0.82435 0.068 0.000 0.928 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6819 0.47990 0.604 0.208 0.000 0.188
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2101 0.86366 0.928 0.000 0.012 0.060
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0707 0.86460 0.980 0.000 0.000 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6124 0.53832 0.640 0.000 0.276 0.084
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 4 0.4535 0.76739 0.000 0.292 0.004 0.704
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.6751 0.13196 0.000 0.396 0.096 0.508
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0921 0.86350 0.972 0.000 0.000 0.028
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1211 0.86006 0.960 0.000 0.000 0.040
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.5119 0.54329 0.112 0.764 0.000 0.124
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.1211 0.68671 0.000 0.960 0.000 0.040
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.5102 0.66134 0.732 0.000 0.220 0.048
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.2469 0.82097 0.000 0.000 0.892 0.108
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0188 0.86761 0.996 0.000 0.000 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2319 0.85610 0.924 0.036 0.000 0.040
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1867 0.67686 0.000 0.928 0.000 0.072
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.5773 0.53220 0.632 0.320 0.000 0.048
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.85361 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.2408 0.82248 0.000 0.000 0.896 0.104
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.6324 0.58172 0.660 0.172 0.000 0.168
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.1545 0.85930 0.952 0.008 0.000 0.040
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 4 0.4661 0.72278 0.000 0.348 0.000 0.652
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.1557 0.86603 0.944 0.000 0.000 0.056
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.1305 0.86283 0.960 0.000 0.004 0.036
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.5386 0.38908 0.000 0.368 0.020 0.612
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.1302 0.85872 0.956 0.000 0.000 0.044
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1474 0.86494 0.948 0.000 0.000 0.052
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1211 0.86553 0.960 0.000 0.000 0.040
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2011 0.68262 0.000 0.920 0.000 0.080
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1637 0.68174 0.000 0.940 0.000 0.060
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5387 0.59074 0.696 0.000 0.256 0.048
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 4 0.4454 0.73336 0.000 0.308 0.000 0.692
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.4277 0.37869 0.000 0.720 0.000 0.280
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0707 0.86769 0.980 0.000 0.000 0.020
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.8683 0.36142 0.492 0.260 0.164 0.084
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0000 0.85361 0.000 0.000 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.4500 0.74912 0.000 0.316 0.000 0.684
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.2142 0.86210 0.928 0.000 0.016 0.056
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.4877 0.35531 0.000 0.408 0.000 0.592
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.5249 0.44240 0.248 0.708 0.000 0.044
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2011 0.68262 0.000 0.920 0.000 0.080
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.6414 0.44848 0.000 0.240 0.124 0.636
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.8420 0.18776 0.480 0.148 0.312 0.060
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.3962 0.78464 0.000 0.044 0.832 0.124
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1305 0.84783 0.004 0.000 0.960 0.036
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.2227 0.84975 0.928 0.036 0.000 0.036
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0592 0.85237 0.000 0.000 0.984 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.0469 0.85191 0.000 0.000 0.988 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.5923 0.25302 0.376 0.580 0.000 0.044
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 4 0.4955 0.74893 0.000 0.268 0.024 0.708
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.8158 0.06211 0.020 0.460 0.224 0.296
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1211 0.86553 0.960 0.000 0.000 0.040
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1474 0.69802 0.000 0.948 0.000 0.052
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.85361 0.000 0.000 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.1474 0.86643 0.948 0.000 0.000 0.052
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1716 0.69953 0.000 0.936 0.000 0.064
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.1557 0.86603 0.944 0.000 0.000 0.056
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.1302 0.85872 0.956 0.000 0.000 0.044
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.4424 0.58019 0.100 0.812 0.000 0.088
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 4 0.4382 0.76647 0.000 0.296 0.000 0.704
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0188 0.86761 0.996 0.000 0.000 0.004
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 4 0.4356 0.76607 0.000 0.292 0.000 0.708
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.4941 -0.24347 0.000 0.564 0.000 0.436
#> 31322670-76A2-4308-A71F-D8E00049519D 4 0.4382 0.76647 0.000 0.296 0.000 0.704
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.5994 0.68374 0.116 0.024 0.732 0.128
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.3873 0.47762 0.000 0.772 0.000 0.228
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.1389 0.86673 0.952 0.000 0.000 0.048
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.5698 0.34917 0.320 0.636 0.000 0.044
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.7043 -0.06547 0.000 0.504 0.128 0.368
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.4890 0.74185 0.776 0.000 0.144 0.080
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.0000 0.85361 0.000 0.000 1.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.5421 0.63726 0.200 0.000 0.724 0.076
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.1022 0.86156 0.968 0.000 0.000 0.032
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.4072 0.39715 0.000 0.748 0.000 0.252
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.1211 0.86553 0.960 0.000 0.000 0.040
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.4500 0.16513 0.000 0.684 0.000 0.316
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.1867 0.67686 0.000 0.928 0.000 0.072
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1474 0.69802 0.000 0.948 0.000 0.052
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.1022 0.86156 0.968 0.000 0.000 0.032
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.5167 0.20576 0.016 0.644 0.000 0.340
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 4 0.4535 0.76739 0.000 0.292 0.004 0.704
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.1118 0.86089 0.964 0.000 0.000 0.036
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.4800 0.27149 0.000 0.656 0.004 0.340
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.6465 0.24513 0.516 0.000 0.412 0.072
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.1716 0.86458 0.936 0.000 0.000 0.064
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.1211 0.69990 0.000 0.960 0.000 0.040
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.1305 0.84522 0.036 0.000 0.960 0.004
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 4 0.4819 0.71099 0.000 0.344 0.004 0.652
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.2124 0.86022 0.924 0.008 0.000 0.068
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.5596 0.49779 0.632 0.332 0.000 0.036
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.4872 0.65707 0.728 0.244 0.000 0.028
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 3 0.2281 0.82588 0.000 0.000 0.904 0.096
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.0817 0.86372 0.976 0.000 0.000 0.024
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 4 0.4382 0.76647 0.000 0.296 0.000 0.704
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.5328 0.60439 0.704 0.000 0.248 0.048
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.1022 0.86156 0.968 0.000 0.000 0.032
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1637 0.86383 0.940 0.000 0.000 0.060
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0592 0.85126 0.000 0.000 0.984 0.016
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 3 0.7632 0.58879 0.116 0.092 0.628 0.164
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.4720 0.33839 0.000 0.720 0.016 0.264
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.2623 0.85412 0.908 0.028 0.000 0.064
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 4 0.4535 0.76739 0.000 0.292 0.004 0.704
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0707 0.85199 0.000 0.000 0.980 0.020
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 1 0.1118 0.86089 0.964 0.000 0.000 0.036
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.3758 0.63125 0.000 0.848 0.104 0.048
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.1557 0.69087 0.000 0.944 0.000 0.056
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.1211 0.86593 0.960 0.000 0.000 0.040
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.3539 0.55982 0.000 0.820 0.004 0.176
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 4 0.4535 0.76739 0.000 0.292 0.004 0.704
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#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.5304 0.67547 0.748 0.104 0.000 0.148
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.2281 0.82588 0.000 0.000 0.904 0.096
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5543 0.33778 0.360 0.000 0.612 0.028
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0336 0.86807 0.992 0.000 0.000 0.008
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2222 0.83336 0.016 0.000 0.924 0.060
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5799 0.60324 0.668 0.264 0.000 0.068
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2408 0.65920 0.000 0.896 0.000 0.104
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.1716 0.86299 0.936 0.000 0.000 0.064
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.4830 0.68339 0.000 0.392 0.000 0.608
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1004 0.84967 0.024 0.000 0.972 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0188 0.86761 0.996 0.000 0.000 0.004
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1118 0.86089 0.964 0.000 0.000 0.036
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.5710 0.62298 0.228 0.008 0.704 0.060
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4164 0.40584 0.000 0.736 0.000 0.264
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0336 0.86807 0.992 0.000 0.000 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.1854 0.85677 0.940 0.000 0.012 0.048
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1557 0.86603 0.944 0.000 0.000 0.056
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.7785 0.06376 0.284 0.288 0.000 0.428
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.6637 0.44304 0.000 0.240 0.144 0.616
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0592 0.85126 0.000 0.000 0.984 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F 4 0.4632 0.75372 0.000 0.308 0.004 0.688
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0921 0.86691 0.972 0.000 0.000 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0188 0.86697 0.996 0.000 0.000 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.1792 0.86453 0.932 0.000 0.000 0.068
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0921 0.86691 0.972 0.000 0.000 0.028
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4197 0.6065 0.000 0.728 0.000 0.028 0.244
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.5131 0.6053 0.148 0.044 0.000 0.740 0.068
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1356 0.6986 0.000 0.012 0.956 0.028 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.6141 0.5097 0.000 0.156 0.032 0.640 0.172
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.3579 0.7842 0.000 0.072 0.000 0.100 0.828
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.6728 0.0301 0.412 0.016 0.436 0.132 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.7260 0.0447 0.440 0.072 0.372 0.116 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.7955 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.8473 0.0588 0.340 0.120 0.356 0.164 0.020
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1041 0.7026 0.000 0.000 0.964 0.032 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.1410 0.8772 0.000 0.060 0.000 0.000 0.940
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.1502 0.7889 0.940 0.000 0.000 0.056 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.1544 0.8766 0.000 0.068 0.000 0.000 0.932
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4149 0.7181 0.792 0.004 0.000 0.080 0.124
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.6956 0.1704 0.412 0.056 0.100 0.432 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.2932 0.7625 0.864 0.020 0.000 0.112 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.5358 0.6095 0.128 0.060 0.000 0.732 0.080
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.1591 0.8706 0.000 0.052 0.004 0.004 0.940
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.6539 0.0548 0.000 0.200 0.000 0.368 0.432
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.1638 0.8788 0.000 0.064 0.000 0.004 0.932
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4622 0.4961 0.000 0.000 0.684 0.276 0.040
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.5977 0.2745 0.000 0.332 0.000 0.128 0.540
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2843 0.7650 0.848 0.000 0.000 0.144 0.008
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5954 0.4328 0.000 0.592 0.000 0.192 0.216
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.1571 0.8766 0.000 0.060 0.004 0.000 0.936
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3732 0.5996 0.120 0.000 0.820 0.056 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 4 0.6470 0.3552 0.392 0.088 0.000 0.488 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.1864 0.7918 0.924 0.004 0.004 0.068 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1341 0.7904 0.944 0.000 0.000 0.056 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.7117 0.3467 0.480 0.008 0.304 0.188 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.1638 0.8788 0.000 0.064 0.000 0.004 0.932
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.5889 0.5295 0.000 0.108 0.096 0.696 0.100
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2116 0.7858 0.912 0.004 0.000 0.076 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2747 0.7704 0.880 0.004 0.008 0.100 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.6105 0.2616 0.060 0.532 0.000 0.376 0.032
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3809 0.5602 0.000 0.736 0.000 0.256 0.008
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6285 0.4885 0.588 0.012 0.256 0.140 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4576 0.4995 0.000 0.000 0.692 0.268 0.040
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0486 0.7963 0.988 0.004 0.000 0.004 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3506 0.7346 0.832 0.064 0.000 0.104 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.4087 0.5794 0.000 0.756 0.000 0.208 0.036
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.2843 0.7650 0.848 0.000 0.000 0.144 0.008
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6056 0.2386 0.556 0.156 0.000 0.288 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0162 0.7041 0.000 0.000 0.996 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4622 0.4962 0.000 0.000 0.684 0.276 0.040
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.6080 0.3555 0.328 0.080 0.000 0.568 0.024
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.2669 0.7690 0.876 0.020 0.000 0.104 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.2388 0.8547 0.000 0.072 0.000 0.028 0.900
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.3213 0.7851 0.836 0.004 0.000 0.144 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.2575 0.7792 0.884 0.012 0.004 0.100 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.6187 0.4741 0.000 0.204 0.016 0.608 0.172
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.2681 0.7681 0.876 0.012 0.000 0.108 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.2439 0.7753 0.876 0.000 0.000 0.120 0.004
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2233 0.7795 0.892 0.000 0.000 0.104 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2304 0.7185 0.000 0.892 0.000 0.008 0.100
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4040 0.5473 0.000 0.724 0.000 0.260 0.016
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.6465 0.3766 0.560 0.016 0.300 0.116 0.008
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.2927 0.8287 0.000 0.068 0.000 0.060 0.872
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1043 0.7939 0.960 0.000 0.000 0.040 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.5133 0.3541 0.000 0.568 0.000 0.388 0.044
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.2753 0.7697 0.856 0.000 0.000 0.136 0.008
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0290 0.7953 0.992 0.000 0.000 0.008 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.8675 0.1074 0.364 0.188 0.244 0.192 0.012
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0865 0.7003 0.000 0.000 0.972 0.024 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.1544 0.8769 0.000 0.068 0.000 0.000 0.932
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0703 0.7940 0.976 0.000 0.000 0.024 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3066 0.7884 0.860 0.004 0.012 0.116 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5638 0.4733 0.000 0.192 0.000 0.636 0.172
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.4908 0.5415 0.156 0.748 0.000 0.068 0.028
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2361 0.7191 0.000 0.892 0.000 0.012 0.096
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.7673 0.4386 0.000 0.176 0.128 0.500 0.196
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.8241 0.0153 0.404 0.156 0.296 0.136 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.5068 0.3120 0.000 0.000 0.572 0.388 0.040
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2452 0.6784 0.000 0.016 0.896 0.084 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.3150 0.7735 0.864 0.024 0.000 0.096 0.016
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0324 0.7038 0.000 0.004 0.992 0.004 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1300 0.6970 0.000 0.000 0.956 0.028 0.016
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.6287 0.1473 0.276 0.528 0.000 0.196 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.1341 0.8739 0.000 0.056 0.000 0.000 0.944
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1082 0.7944 0.964 0.008 0.000 0.028 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.8694 0.0830 0.060 0.408 0.296 0.120 0.116
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.2020 0.7806 0.900 0.000 0.000 0.100 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1965 0.7204 0.000 0.904 0.000 0.000 0.096
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0324 0.7032 0.000 0.000 0.992 0.004 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.3111 0.7845 0.840 0.004 0.000 0.144 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.2249 0.7194 0.000 0.896 0.000 0.008 0.096
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.3299 0.7854 0.828 0.004 0.000 0.152 0.016
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.2570 0.7694 0.880 0.008 0.000 0.108 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.5050 0.4874 0.024 0.660 0.000 0.292 0.024
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.1638 0.8788 0.000 0.064 0.000 0.004 0.932
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0613 0.7965 0.984 0.004 0.000 0.008 0.004
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.1410 0.8772 0.000 0.060 0.000 0.000 0.940
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.6700 0.0388 0.000 0.400 0.000 0.356 0.244
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.1638 0.8788 0.000 0.064 0.000 0.004 0.932
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.5588 0.2930 0.020 0.000 0.560 0.380 0.040
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.2522 0.7159 0.000 0.880 0.000 0.012 0.108
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.2886 0.7804 0.864 0.004 0.000 0.116 0.016
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.2843 0.7662 0.848 0.000 0.000 0.144 0.008
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.4735 0.5002 0.172 0.748 0.000 0.064 0.016
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.7870 0.1950 0.000 0.468 0.224 0.152 0.156
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.5431 0.6257 0.696 0.004 0.136 0.156 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.0865 0.7003 0.000 0.000 0.972 0.024 0.004
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.5861 0.4540 0.148 0.012 0.680 0.144 0.016
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.2170 0.7802 0.904 0.004 0.000 0.088 0.004
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.2707 0.7035 0.000 0.860 0.000 0.008 0.132
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.1908 0.7829 0.908 0.000 0.000 0.092 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 5 0.6879 0.0105 0.028 0.384 0.000 0.144 0.444
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.4382 0.5131 0.000 0.688 0.000 0.288 0.024
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.2124 0.7202 0.000 0.900 0.000 0.004 0.096
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.2011 0.7801 0.908 0.000 0.000 0.088 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.7516 0.1213 0.048 0.428 0.000 0.244 0.280
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 5 0.1478 0.8786 0.000 0.064 0.000 0.000 0.936
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.2408 0.7747 0.892 0.004 0.000 0.096 0.008
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.5166 0.5583 0.000 0.692 0.004 0.204 0.100
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.7045 0.1571 0.424 0.012 0.388 0.164 0.012
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0794 0.7936 0.972 0.000 0.000 0.028 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.4035 0.7770 0.780 0.004 0.012 0.188 0.016
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.2505 0.7202 0.000 0.888 0.000 0.020 0.092
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.3223 0.6524 0.072 0.004 0.868 0.048 0.008
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#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.7084 0.4483 0.488 0.008 0.272 0.216 0.016
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.2389 0.7768 0.880 0.000 0.000 0.116 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.2660 0.7062 0.000 0.864 0.000 0.008 0.128
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.4219 0.1936 0.000 0.584 0.000 0.000 0.416
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.5338 0.6106 0.132 0.056 0.000 0.732 0.080
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.1041 0.7026 0.000 0.000 0.964 0.032 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.2753 0.7697 0.856 0.000 0.000 0.136 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.2237 0.7806 0.904 0.004 0.000 0.084 0.008
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0992 0.6995 0.000 0.000 0.968 0.024 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2054 0.7832 0.916 0.004 0.000 0.072 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.6404 0.3721 0.556 0.008 0.308 0.116 0.012
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0290 0.7032 0.000 0.000 0.992 0.008 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.3631 0.7799 0.804 0.000 0.012 0.172 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0290 0.7953 0.992 0.000 0.000 0.008 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0162 0.7954 0.996 0.000 0.000 0.004 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2700 0.7197 0.004 0.884 0.000 0.024 0.088
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.6733 0.4303 0.000 0.584 0.096 0.240 0.080
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5971 0.4180 0.588 0.292 0.004 0.112 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.5607 0.4388 0.000 0.312 0.604 0.076 0.008
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0963 0.7927 0.964 0.000 0.000 0.036 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.1965 0.8459 0.024 0.052 0.000 0.000 0.924
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.2305 0.7199 0.000 0.896 0.000 0.012 0.092
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2843 0.7650 0.848 0.000 0.000 0.144 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1502 0.7889 0.940 0.000 0.000 0.056 0.004
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2727 0.6693 0.016 0.004 0.884 0.092 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3123 0.7863 0.828 0.000 0.000 0.160 0.012
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.4731 0.4555 0.000 0.640 0.000 0.328 0.032
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3013 0.7617 0.832 0.000 0.000 0.160 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.6696 0.2033 0.004 0.468 0.000 0.236 0.292
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.2753 0.7695 0.856 0.000 0.000 0.136 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.2753 0.7689 0.856 0.000 0.000 0.136 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5335 0.6201 0.704 0.004 0.184 0.096 0.012
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4404 0.5180 0.000 0.000 0.712 0.252 0.036
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.1341 0.7898 0.944 0.000 0.000 0.056 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2804 0.7757 0.880 0.004 0.012 0.096 0.008
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.5513 0.4762 0.000 0.180 0.000 0.652 0.168
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.5939 0.5127 0.036 0.084 0.000 0.240 0.640
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.2352 0.7160 0.000 0.896 0.004 0.008 0.092
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.6081 0.2218 0.428 0.036 0.000 0.488 0.048
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4477 0.5148 0.000 0.000 0.708 0.252 0.040
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5172 0.2396 0.324 0.000 0.616 0.060 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0833 0.7972 0.976 0.004 0.000 0.016 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4609 0.5993 0.072 0.016 0.776 0.132 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.6372 0.4547 0.552 0.260 0.000 0.180 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4874 0.4031 0.000 0.600 0.000 0.368 0.032
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2886 0.7641 0.844 0.000 0.000 0.148 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.2853 0.8345 0.000 0.072 0.000 0.052 0.876
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1757 0.6970 0.012 0.000 0.936 0.048 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.7955 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.2295 0.7817 0.900 0.004 0.000 0.088 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.7133 0.3204 0.292 0.052 0.516 0.136 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.5672 0.3343 0.000 0.544 0.000 0.368 0.088
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1202 0.7978 0.960 0.004 0.000 0.032 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2983 0.7795 0.872 0.008 0.012 0.100 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3381 0.7860 0.820 0.004 0.000 0.160 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1121 0.7925 0.956 0.000 0.000 0.044 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.5376 0.6080 0.124 0.064 0.000 0.732 0.080
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1270 0.7926 0.948 0.000 0.000 0.052 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.8196 0.3901 0.000 0.176 0.200 0.416 0.208
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1403 0.6955 0.000 0.000 0.952 0.024 0.024
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.2305 0.8546 0.000 0.092 0.000 0.012 0.896
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0609 0.7943 0.980 0.000 0.000 0.020 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0566 0.7969 0.984 0.000 0.000 0.012 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3648 0.7817 0.792 0.004 0.000 0.188 0.016
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1205 0.7941 0.956 0.000 0.000 0.040 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5798 0.46624 0.012 0.620 0.032 0.016 0.264 0.056
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.5590 0.27792 0.072 0.028 0.000 0.220 0.028 0.652
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2668 0.36148 0.000 0.000 0.828 0.168 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.6459 0.25834 0.000 0.088 0.004 0.508 0.088 0.312
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.2963 0.74653 0.000 0.016 0.000 0.004 0.828 0.152
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.3957 0.41265 0.284 0.008 0.696 0.004 0.000 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.6237 0.20797 0.356 0.096 0.492 0.004 0.000 0.052
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1075 0.73003 0.952 0.000 0.000 0.000 0.000 0.048
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.6414 0.29951 0.296 0.072 0.532 0.004 0.004 0.092
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4531 0.22551 0.036 0.000 0.608 0.352 0.000 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0291 0.87564 0.000 0.004 0.000 0.000 0.992 0.004
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0632 0.71778 0.976 0.000 0.024 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.0291 0.87564 0.000 0.004 0.000 0.000 0.992 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4088 0.61737 0.780 0.000 0.100 0.000 0.100 0.020
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.6354 0.36629 0.164 0.044 0.120 0.052 0.000 0.620
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.3328 0.60433 0.788 0.012 0.192 0.000 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.5630 0.25605 0.048 0.032 0.000 0.236 0.040 0.644
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0436 0.87312 0.000 0.004 0.000 0.004 0.988 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.6453 0.12886 0.000 0.104 0.000 0.076 0.460 0.360
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0508 0.87592 0.000 0.004 0.000 0.012 0.984 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.3782 0.50378 0.000 0.000 0.224 0.740 0.000 0.036
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.5561 0.42834 0.000 0.200 0.000 0.016 0.608 0.176
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.3390 0.67491 0.704 0.000 0.000 0.000 0.000 0.296
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.6515 0.31411 0.000 0.516 0.000 0.276 0.108 0.100
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.0405 0.87611 0.000 0.004 0.000 0.008 0.988 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5083 0.21858 0.100 0.000 0.580 0.320 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 6 0.6483 0.43157 0.220 0.084 0.000 0.124 0.008 0.564
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3658 0.70144 0.792 0.000 0.104 0.000 0.000 0.104
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1408 0.72715 0.944 0.000 0.020 0.000 0.000 0.036
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.5712 0.15471 0.340 0.000 0.512 0.000 0.008 0.140
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0508 0.87592 0.000 0.004 0.000 0.012 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.5746 0.25443 0.000 0.044 0.020 0.492 0.028 0.416
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2163 0.68313 0.892 0.000 0.092 0.000 0.000 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3277 0.60634 0.792 0.000 0.188 0.000 0.004 0.016
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 6 0.5235 0.25392 0.004 0.420 0.000 0.060 0.008 0.508
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4955 -0.04182 0.000 0.520 0.000 0.056 0.004 0.420
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.4374 0.08485 0.448 0.000 0.532 0.004 0.000 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.4680 0.49483 0.000 0.000 0.264 0.652 0.000 0.084
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0865 0.73016 0.964 0.000 0.000 0.000 0.000 0.036
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.6066 0.13241 0.504 0.064 0.020 0.036 0.000 0.376
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.5028 -0.00288 0.000 0.536 0.000 0.056 0.008 0.400
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3409 0.67277 0.700 0.000 0.000 0.000 0.000 0.300
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 6 0.6091 0.43185 0.216 0.180 0.000 0.040 0.000 0.564
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3619 0.26808 0.000 0.000 0.680 0.316 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.3852 0.48700 0.000 0.004 0.224 0.740 0.000 0.032
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.7236 0.38008 0.176 0.076 0.064 0.132 0.004 0.548
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3385 0.65102 0.808 0.016 0.156 0.000 0.000 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.1493 0.84576 0.000 0.004 0.000 0.004 0.936 0.056
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.3642 0.70495 0.760 0.000 0.036 0.000 0.000 0.204
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3660 0.67462 0.780 0.000 0.160 0.000 0.000 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.6587 0.27315 0.000 0.140 0.000 0.508 0.084 0.268
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.3198 0.61121 0.796 0.008 0.188 0.000 0.000 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.3221 0.68910 0.736 0.000 0.000 0.000 0.000 0.264
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2996 0.70198 0.772 0.000 0.000 0.000 0.000 0.228
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2263 0.71087 0.000 0.896 0.000 0.048 0.056 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.5074 -0.10191 0.000 0.496 0.000 0.056 0.008 0.440
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.4462 0.09342 0.540 0.008 0.436 0.000 0.000 0.016
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.1901 0.82920 0.000 0.004 0.000 0.008 0.912 0.076
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.2979 0.71825 0.840 0.000 0.044 0.000 0.000 0.116
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 6 0.5508 0.27037 0.000 0.400 0.000 0.092 0.012 0.496
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3753 0.67311 0.696 0.004 0.000 0.008 0.000 0.292
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.1858 0.72737 0.904 0.000 0.004 0.000 0.000 0.092
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.7017 0.29254 0.192 0.132 0.540 0.028 0.000 0.108
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3695 0.20236 0.000 0.000 0.624 0.376 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.0436 0.87570 0.000 0.004 0.000 0.004 0.988 0.004
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2386 0.72323 0.876 0.004 0.004 0.004 0.000 0.112
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4931 0.65059 0.648 0.000 0.136 0.000 0.000 0.216
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.6534 0.25435 0.000 0.116 0.000 0.500 0.088 0.296
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.4842 0.56203 0.080 0.760 0.092 0.012 0.008 0.048
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2201 0.71090 0.000 0.900 0.000 0.048 0.052 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.7059 0.35427 0.000 0.132 0.032 0.540 0.108 0.188
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.5032 0.29309 0.376 0.060 0.556 0.000 0.000 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.5434 0.52858 0.000 0.000 0.232 0.576 0.000 0.192
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1908 0.39464 0.000 0.000 0.900 0.096 0.000 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.3989 0.63105 0.796 0.032 0.132 0.000 0.016 0.024
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#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.4478 0.63956 0.724 0.000 0.168 0.000 0.008 0.100
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.1151 0.72816 0.956 0.000 0.012 0.000 0.000 0.032
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.2941 0.33657 0.000 0.000 0.780 0.220 0.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.5164 0.32058 0.000 0.024 0.036 0.556 0.004 0.380
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 5 0.0000 0.87493 0.000 0.000 0.000 0.000 1.000 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.2263 0.71087 0.000 0.896 0.000 0.048 0.056 0.000
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#> 80936433-AA91-4219-98F1-706C36298060 4 0.3888 0.49417 0.000 0.012 0.200 0.756 0.000 0.032
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.7172 0.35281 0.100 0.000 0.200 0.376 0.000 0.324
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#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.4179 0.02521 0.516 0.000 0.472 0.000 0.000 0.012
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#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.5956 0.46738 0.632 0.108 0.180 0.008 0.000 0.072
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.0000 0.87493 0.000 0.000 0.000 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 5 0.5327 0.43844 0.000 0.220 0.000 0.008 0.620 0.152
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4062 0.65483 0.660 0.000 0.024 0.000 0.000 0.316
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4943 0.20308 0.056 0.000 0.576 0.360 0.000 0.008
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.5939 -0.06139 0.392 0.000 0.436 0.000 0.008 0.164
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.3151 0.69199 0.748 0.000 0.000 0.000 0.000 0.252
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.2644 0.70531 0.000 0.880 0.000 0.052 0.060 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.3993 0.52405 0.000 0.700 0.000 0.024 0.272 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 6 0.5669 0.25696 0.048 0.032 0.000 0.232 0.044 0.644
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4206 0.22738 0.024 0.000 0.620 0.356 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.3499 0.66421 0.680 0.000 0.000 0.000 0.000 0.320
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.2404 0.67142 0.872 0.000 0.112 0.000 0.000 0.016
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.3727 0.18622 0.000 0.000 0.612 0.388 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2358 0.67446 0.876 0.000 0.108 0.000 0.000 0.016
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.4462 0.08893 0.540 0.000 0.436 0.000 0.008 0.016
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.3647 0.22112 0.000 0.000 0.640 0.360 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.5346 0.54336 0.584 0.000 0.252 0.000 0.000 0.164
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.1753 0.72832 0.912 0.000 0.004 0.000 0.000 0.084
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.1141 0.72992 0.948 0.000 0.000 0.000 0.000 0.052
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2706 0.68840 0.000 0.876 0.000 0.008 0.056 0.060
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.7306 0.31575 0.000 0.520 0.104 0.164 0.044 0.168
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5671 0.39921 0.624 0.140 0.204 0.004 0.000 0.028
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4367 0.27058 0.000 0.220 0.712 0.060 0.000 0.008
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.2092 0.72108 0.876 0.000 0.000 0.000 0.000 0.124
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0405 0.86734 0.008 0.000 0.000 0.000 0.988 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.2134 0.71192 0.000 0.904 0.000 0.044 0.052 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0632 0.71778 0.976 0.000 0.024 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3265 0.39615 0.056 0.000 0.828 0.112 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.4603 0.66232 0.696 0.000 0.156 0.000 0.000 0.148
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 6 0.5114 0.22192 0.000 0.440 0.000 0.068 0.004 0.488
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.3499 0.66252 0.680 0.000 0.000 0.000 0.000 0.320
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4269 0.64773 0.648 0.000 0.036 0.000 0.000 0.316
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 6 0.6660 0.26039 0.000 0.272 0.000 0.032 0.304 0.392
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.3428 0.67141 0.696 0.000 0.000 0.000 0.000 0.304
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4195 0.36944 0.648 0.000 0.328 0.000 0.008 0.016
#> 1122039D-5785-4F70-9916-17C585453512 4 0.4552 0.47523 0.000 0.000 0.288 0.648 0.000 0.064
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.1408 0.72715 0.944 0.000 0.020 0.000 0.000 0.036
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2996 0.64525 0.832 0.000 0.144 0.000 0.008 0.016
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.6320 0.22406 0.000 0.084 0.000 0.504 0.088 0.324
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.4934 0.43455 0.040 0.012 0.000 0.008 0.616 0.324
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.1863 0.71468 0.000 0.924 0.004 0.008 0.056 0.008
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.6916 0.10324 0.400 0.028 0.020 0.108 0.024 0.420
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.4673 0.48862 0.000 0.000 0.272 0.648 0.000 0.080
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.7209 0.00554 0.216 0.000 0.404 0.272 0.000 0.108
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1387 0.73355 0.932 0.000 0.000 0.000 0.000 0.068
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2320 0.44510 0.080 0.000 0.892 0.024 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.7341 0.28747 0.444 0.232 0.128 0.008 0.000 0.188
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 6 0.5308 0.25345 0.000 0.424 0.000 0.088 0.004 0.484
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.3482 0.66493 0.684 0.000 0.000 0.000 0.000 0.316
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.1588 0.83368 0.000 0.004 0.000 0.000 0.924 0.072
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4518 0.22388 0.044 0.000 0.604 0.352 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.1075 0.73003 0.952 0.000 0.000 0.000 0.000 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.2712 0.66885 0.864 0.000 0.108 0.000 0.012 0.016
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3620 0.44394 0.228 0.012 0.752 0.004 0.000 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 6 0.5925 0.27080 0.000 0.396 0.000 0.100 0.032 0.472
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1700 0.73513 0.916 0.000 0.004 0.000 0.000 0.080
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3345 0.62690 0.776 0.000 0.204 0.000 0.000 0.020
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4703 0.68226 0.692 0.000 0.096 0.000 0.008 0.204
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2378 0.71919 0.848 0.000 0.000 0.000 0.000 0.152
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.5728 0.25303 0.048 0.032 0.000 0.232 0.048 0.640
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3083 0.71604 0.828 0.000 0.040 0.000 0.000 0.132
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.7387 0.34885 0.000 0.136 0.068 0.524 0.096 0.176
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3817 0.11351 0.000 0.000 0.568 0.432 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.2744 0.79150 0.000 0.072 0.000 0.064 0.864 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2053 0.72441 0.888 0.000 0.004 0.000 0.000 0.108
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0820 0.72491 0.972 0.000 0.012 0.000 0.000 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5268 0.62282 0.620 0.000 0.164 0.000 0.004 0.212
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2416 0.72107 0.844 0.000 0.000 0.000 0.000 0.156
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.704 0.808 0.925 0.4982 0.500 0.500
#> 3 3 0.777 0.832 0.932 0.3070 0.756 0.552
#> 4 4 0.772 0.797 0.908 0.1178 0.887 0.690
#> 5 5 0.696 0.644 0.814 0.0662 0.942 0.798
#> 6 6 0.708 0.465 0.740 0.0505 0.898 0.619
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.88900 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.9710 0.31264 0.600 0.400
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.1633 0.87357 0.024 0.976
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.88900 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.88900 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.93329 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.8443 0.58691 0.728 0.272
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.93329 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.8763 0.58698 0.296 0.704
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.9710 0.23892 0.600 0.400
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.88900 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.93329 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.88900 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0000 0.93329 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.9248 0.45148 0.660 0.340
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.93329 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.9710 0.31264 0.600 0.400
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.88900 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.88900 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.88900 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.88900 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.88900 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.93329 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.88900 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.93329 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.88900 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.93329 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.9710 0.31264 0.600 0.400
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.93329 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.93329 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0000 0.93329 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.88900 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.88900 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.93329 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.93329 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.9710 0.31264 0.600 0.400
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.88900 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.93329 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.93329 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.0000 0.88900 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.93329 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.93329 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.88900 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.93329 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6973 0.71686 0.812 0.188
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.9710 0.39622 0.400 0.600
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.88900 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.9896 0.20070 0.560 0.440
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.93329 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.88900 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.93329 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.93329 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.88900 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.93329 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.93329 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.93329 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.88900 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.9710 0.32086 0.400 0.600
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.9710 0.23892 0.600 0.400
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.88900 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.93329 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.88900 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.93329 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.93329 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.9460 0.34015 0.636 0.364
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.9661 0.41318 0.392 0.608
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.88900 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.93329 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.93329 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.93329 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.88900 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.9850 0.24515 0.428 0.572
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.88900 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.88900 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.9977 0.20026 0.472 0.528
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.0000 0.88900 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.9881 0.30549 0.436 0.564
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.9248 0.41298 0.660 0.340
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.9710 0.39622 0.400 0.600
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.88900 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.2948 0.88335 0.948 0.052
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.88900 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.93329 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.0000 0.88900 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.93329 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.88900 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.93329 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.8327 0.63339 0.264 0.736
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.93329 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.88900 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.93329 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.0000 0.93329 1.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.9710 0.31264 0.600 0.400
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.88900 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.93329 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0000 0.88900 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.88900 0.000 1.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.88900 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 2 0.9661 0.34055 0.392 0.608
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.88900 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.93329 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.93329 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.8713 0.55709 0.708 0.292
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.88900 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0000 0.93329 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.8861 0.57425 0.304 0.696
#> D09064DF-70AE-4A49-9F70-2A8093C96724 2 0.9248 0.51361 0.340 0.660
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0000 0.93329 1.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.88900 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.93329 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.4939 0.80047 0.108 0.892
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.2778 0.85410 0.048 0.952
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.88900 0.000 1.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.0000 0.93329 1.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.9963 0.13352 0.464 0.536
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.88900 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0000 0.93329 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.88900 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.9954 0.03606 0.540 0.460
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.93329 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0000 0.93329 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.93329 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0000 0.88900 0.000 1.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.0000 0.93329 1.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0000 0.88900 0.000 1.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.0000 0.93329 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.1414 0.91513 0.980 0.020
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.0000 0.93329 1.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.93329 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.0000 0.88900 0.000 1.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.0000 0.93329 1.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.88900 0.000 1.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.9710 0.23892 0.600 0.400
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.0000 0.93329 1.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.0000 0.93329 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 2 0.4939 0.80752 0.108 0.892
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 2 0.7883 0.64308 0.236 0.764
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.88900 0.000 1.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.0000 0.93329 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.88900 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 2 0.9710 0.39622 0.400 0.600
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 1 0.0376 0.92968 0.996 0.004
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.88900 0.000 1.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.88900 0.000 1.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.0000 0.93329 1.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.88900 0.000 1.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.88900 0.000 1.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0000 0.93329 1.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 1 0.2043 0.90284 0.968 0.032
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.0000 0.93329 1.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.88900 0.000 1.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 2 0.9710 0.39622 0.400 0.600
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 1 0.9970 0.00531 0.532 0.468
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.0000 0.93329 1.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 1 0.0000 0.93329 1.000 0.000
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.0000 0.93329 1.000 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.0000 0.93329 1.000 0.000
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 1 0.0000 0.93329 1.000 0.000
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#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.0000 0.93329 1.000 0.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.88900 0.000 1.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.88900 0.000 1.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0000 0.88900 0.000 1.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.0000 0.93329 1.000 0.000
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.88900 0.000 1.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.0000 0.93329 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 2 0.9710 0.39622 0.400 0.600
#> 985FEEC2-9737-4018-80DF-21A07AB47900 1 0.0000 0.93329 1.000 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.0000 0.93329 1.000 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.0000 0.93329 1.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.88900 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.88900 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.0000 0.93329 1.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.0000 0.88900 0.000 1.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.9710 0.39622 0.400 0.600
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0000 0.93329 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.88900 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.93329 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 2 0.9710 0.39622 0.400 0.600
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0000 0.93329 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.88900 0.000 1.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.0000 0.93329 1.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.93329 1.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.0672 0.88410 0.008 0.992
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.0000 0.88900 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0000 0.88900 0.000 1.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.88900 0.000 1.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.9970 0.00539 0.532 0.468
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.9795 0.26968 0.584 0.416
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.88900 0.000 1.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0000 0.88900 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.9710 0.31264 0.600 0.400
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.88900 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.93329 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.93329 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.0000 0.93329 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.93329 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.7219 0.71434 0.200 0.800
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.88900 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.88900 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.88900 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.88900 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.7376 0.68798 0.792 0.208
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.0000 0.93329 1.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.93329 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.93329 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.88900 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.93329 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.93329 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.93329 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.93329 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.93329 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.9710 0.39622 0.400 0.600
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.9710 0.23892 0.600 0.400
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.9866 0.22325 0.568 0.432
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.93329 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.93329 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.88900 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.93329 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0000 0.93329 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0000 0.93329 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.93329 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.93329 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0000 0.93329 1.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.93329 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.9710 0.32086 0.400 0.600
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.8016 0.63144 0.756 0.244
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.88900 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.88900 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.93329 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.8443 0.58651 0.272 0.728
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.0000 0.93329 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.9044 0.54813 0.320 0.680
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.93329 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.9686 0.33097 0.396 0.604
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.9710 0.31264 0.600 0.400
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.93329 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.6438 0.76493 0.836 0.164
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.88900 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.88900 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.93329 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.93329 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.93329 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.93329 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.88900 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.88900 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.9963 0.13352 0.464 0.536
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.1184 0.91844 0.984 0.016
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.93329 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.93329 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.9491 0.46155 0.368 0.632
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.93329 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.9710 0.23892 0.600 0.400
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0938 0.88150 0.012 0.988
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0000 0.93329 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.93329 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.93329 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.9710 0.32086 0.400 0.600
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0000 0.88900 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3584 0.86397 0.932 0.068
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.88900 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.93329 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.88900 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.88900 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.93329 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.93329 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.93329 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.93329 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.93329 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0376 0.88637 0.004 0.996
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.93329 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.93329 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.93329 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.9710 0.32086 0.400 0.600
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.93329 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.93329 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.93329 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 2 0.0000 0.88900 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.93329 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.93329 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.88900 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.88900 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.88900 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.8144 0.61828 0.748 0.252
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.0000 0.88900 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.93329 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.93329 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.9710 0.39622 0.400 0.600
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.93329 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.88900 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.93329 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.3879 0.83014 0.076 0.924
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.93329 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.93329 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.93329 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.2778 0.88613 0.952 0.048
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.88900 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.93329 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.93329 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.93329 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.93329 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.9963 0.13352 0.464 0.536
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.93329 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.88900 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.1184 0.87889 0.016 0.984
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.88900 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.93329 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.93329 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.93329 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.93329 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9334 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.6095 0.3145 0.608 0.392 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8825 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.9334 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9334 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.8825 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.4842 0.6576 0.224 0.000 0.776
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9315 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.8631 0.5600 0.220 0.180 0.600
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.8825 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.9334 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.9315 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9334 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.3038 0.8257 0.896 0.104 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6126 0.3364 0.600 0.000 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.9315 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.6126 0.3656 0.400 0.600 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.2537 0.8556 0.000 0.920 0.080
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.9334 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9334 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.8825 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9334 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9315 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9334 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9315 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9334 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.8825 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.6274 0.2039 0.456 0.544 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4555 0.7140 0.800 0.000 0.200
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9315 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.6095 0.4082 0.392 0.000 0.608
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9334 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0747 0.9195 0.000 0.984 0.016
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#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0000 0.8825 0.000 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.9334 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.9334 0.000 1.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9334 0.000 1.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 3 0.5968 0.4009 0.000 0.364 0.636
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.6244 0.2266 0.560 0.000 0.440
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.0000 0.9315 1.000 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9315 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9315 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9334 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9315 1.000 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9315 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9315 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.9315 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9315 1.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.8825 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5529 0.5832 0.296 0.000 0.704
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.6126 0.3656 0.400 0.600 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.9315 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9315 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.5835 0.4536 0.000 0.340 0.660
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.9315 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0000 0.9315 1.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.8825 0.000 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.9315 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.9315 1.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0000 0.9315 1.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9315 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0000 0.9334 0.000 1.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.5016 0.6515 0.760 0.240 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.8825 0.000 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9334 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.6126 0.3364 0.600 0.000 0.400
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.9334 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.6154 0.3728 0.408 0.000 0.592
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.8825 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9315 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9334 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.6111 0.3032 0.604 0.396 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9315 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.6244 0.2458 0.440 0.560 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9334 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9334 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9315 1.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.8825 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.0000 0.8825 0.000 0.000 1.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9315 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9334 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9334 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.5948 0.4592 0.360 0.640 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8825 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9315 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.9315 1.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8825 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.9315 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.6126 0.3918 0.400 0.000 0.600
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.8825 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4504 0.7119 0.804 0.000 0.196
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9315 1.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.9315 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.9334 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0000 0.9334 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4483 0.7830 0.848 0.024 0.128
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0000 0.8825 0.000 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9315 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9334 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9334 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9315 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.9315 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.8825 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9315 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.9315 1.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.9334 0.000 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.9315 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.9315 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9315 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.9334 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9315 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9315 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6111 0.2695 0.604 0.000 0.396
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0000 0.8825 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9315 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4555 0.7058 0.800 0.000 0.200
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.9334 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.9334 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9334 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4931 0.6629 0.768 0.232 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0000 0.8825 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.4842 0.6576 0.224 0.000 0.776
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9315 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.8825 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.9315 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9334 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9315 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9334 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.8825 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9315 1.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.9315 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.8825 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9334 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9315 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4555 0.7140 0.800 0.000 0.200
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9315 1.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9315 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.4605 0.7148 0.204 0.796 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9315 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9334 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8825 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9334 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9315 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9315 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4555 0.7058 0.800 0.000 0.200
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9315 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0817 0.8814 0.000 0.976 0.000 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.6592 0.1103 0.524 0.392 0.000 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.2081 0.8636 0.000 0.916 0.000 0.084
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0336 0.8849 0.000 0.992 0.000 0.008
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.4855 0.2612 0.000 0.000 0.600 0.400
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.7130 0.4662 0.200 0.008 0.596 0.196
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.4877 0.2955 0.408 0.592 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5816 0.2839 0.572 0.000 0.392 0.036
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4331 0.5670 0.712 0.000 0.000 0.288
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.5938 0.6311 0.232 0.676 0.000 0.092
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0188 0.8857 0.000 0.996 0.004 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1118 0.8768 0.000 0.964 0.000 0.036
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0188 0.8864 0.000 0.996 0.000 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1792 0.8633 0.000 0.932 0.000 0.068
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.6446 0.4937 0.328 0.584 0.000 0.088
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3610 0.7087 0.800 0.000 0.200 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4855 0.3726 0.400 0.000 0.600 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.2466 0.8577 0.000 0.900 0.004 0.096
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2760 0.8076 0.872 0.000 0.128 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.0336 0.8820 0.000 0.008 0.000 0.992
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 4 0.0000 0.8832 0.000 0.000 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.0376 0.8460 0.000 0.004 0.992 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1022 0.9107 0.968 0.000 0.000 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 4 0.1118 0.8844 0.000 0.036 0.000 0.964
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.1474 0.8569 0.052 0.000 0.000 0.948
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.6429 0.6235 0.232 0.660 0.012 0.096
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.3873 0.6743 0.772 0.000 0.000 0.228
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3610 0.7087 0.800 0.000 0.200 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2011 0.8633 0.000 0.920 0.000 0.080
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.2845 0.8454 0.896 0.000 0.076 0.028
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0592 0.9206 0.984 0.000 0.000 0.016
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 4 0.1211 0.8855 0.000 0.040 0.000 0.960
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#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.5000 0.2095 0.000 0.504 0.000 0.496
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 4 0.1022 0.8876 0.000 0.032 0.000 0.968
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0188 0.8863 0.000 0.996 0.000 0.004
#> 80936433-AA91-4219-98F1-706C36298060 3 0.4992 0.0431 0.000 0.476 0.524 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 3 0.5778 0.0476 0.472 0.000 0.500 0.028
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.1637 0.8850 0.940 0.060 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.1867 0.8656 0.000 0.928 0.000 0.072
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 4 0.2216 0.8286 0.092 0.000 0.000 0.908
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.4382 0.5702 0.296 0.000 0.704 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.5938 0.6311 0.232 0.676 0.000 0.092
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.3610 0.7228 0.800 0.000 0.000 0.200
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 4 0.4163 0.7330 0.000 0.020 0.188 0.792
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.3764 0.7080 0.216 0.000 0.000 0.784
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.4134 0.6578 0.260 0.000 0.000 0.740
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 4 0.0817 0.8878 0.000 0.024 0.000 0.976
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.6454 0.2648 0.572 0.344 0.000 0.084
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.3907 0.7218 0.000 0.768 0.000 0.232
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4843 0.3350 0.604 0.000 0.396 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 4 0.0921 0.8879 0.000 0.028 0.000 0.972
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.4888 0.3434 0.412 0.000 0.588 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 4 0.0921 0.8879 0.000 0.028 0.000 0.972
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.5489 0.6346 0.240 0.700 0.000 0.060
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 4 0.4327 0.6916 0.216 0.016 0.000 0.768
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 4 0.4605 0.4680 0.000 0.336 0.000 0.664
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.4925 0.2876 0.000 0.572 0.000 0.428
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.5128 0.7326 0.148 0.760 0.000 0.092
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.4855 0.3726 0.400 0.000 0.600 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.2973 0.7880 0.856 0.000 0.144 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 4 0.0817 0.8878 0.000 0.024 0.000 0.976
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.2334 0.8578 0.000 0.908 0.004 0.088
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 4 0.4008 0.6807 0.244 0.000 0.000 0.756
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.2149 0.7840 0.000 0.000 0.912 0.088
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 4 0.1022 0.8876 0.000 0.032 0.000 0.968
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0336 0.8820 0.000 0.008 0.000 0.992
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0188 0.9289 0.996 0.000 0.000 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0592 0.9207 0.984 0.000 0.000 0.016
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.3219 0.7857 0.000 0.836 0.000 0.164
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4643 0.4232 0.656 0.000 0.344 0.000
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0188 0.8479 0.000 0.000 0.996 0.004
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2704 0.8125 0.876 0.000 0.124 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.2345 0.8569 0.000 0.900 0.000 0.100
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0817 0.8794 0.000 0.976 0.000 0.024
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 4 0.1022 0.8876 0.000 0.032 0.000 0.968
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.6396 0.3772 0.380 0.548 0.000 0.072
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0188 0.8479 0.000 0.000 0.996 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.4431 0.5240 0.304 0.000 0.696 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 4 0.2345 0.8263 0.100 0.000 0.000 0.900
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 4 0.3444 0.6980 0.000 0.184 0.000 0.816
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0336 0.8849 0.000 0.992 0.000 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0188 0.9289 0.996 0.004 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.2345 0.8567 0.000 0.900 0.000 0.100
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3610 0.7087 0.800 0.000 0.200 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.4426 0.7888 0.096 0.812 0.000 0.092
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.1978 0.8666 0.000 0.928 0.004 0.068
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8498 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.8871 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9315 1.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.2149 0.8529 0.912 0.000 0.088 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9315 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.1043 0.8339 0.000 0.040 0.000 0.000 0.960
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4191 0.6762 0.012 0.044 0.000 0.784 0.160
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4885 0.6136 0.000 0.056 0.000 0.668 0.276
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1197 0.7157 0.048 0.000 0.952 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.4557 0.2229 0.000 0.404 0.584 0.012 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.7014 0.4024 0.052 0.224 0.560 0.160 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.3519 0.5667 0.216 0.000 0.000 0.008 0.776
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.4690 0.5003 0.048 0.004 0.240 0.708 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.1830 0.7466 0.924 0.068 0.000 0.008 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4510 0.6789 0.008 0.056 0.000 0.752 0.184
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0162 0.8616 0.000 0.000 0.004 0.000 0.996
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.3835 0.5179 0.000 0.008 0.000 0.260 0.732
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4161 0.2268 0.000 0.000 0.608 0.392 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.3636 0.7660 0.728 0.000 0.000 0.272 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.5409 0.4033 0.000 0.304 0.000 0.084 0.612
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 4 0.7332 0.4094 0.292 0.056 0.000 0.476 0.176
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2358 0.7386 0.888 0.000 0.104 0.008 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.5787 0.4007 0.152 0.000 0.608 0.240 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4769 0.6328 0.000 0.056 0.000 0.688 0.256
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0290 0.7884 0.992 0.000 0.000 0.008 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3427 0.6018 0.796 0.000 0.192 0.012 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.3838 0.6288 0.000 0.716 0.000 0.280 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3395 0.6683 0.000 0.764 0.000 0.236 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4235 0.1543 0.000 0.000 0.576 0.424 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3366 0.7250 0.784 0.004 0.000 0.212 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.3612 0.6717 0.000 0.764 0.000 0.228 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3636 0.7660 0.728 0.000 0.000 0.272 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.4465 0.5878 0.024 0.672 0.000 0.304 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4101 0.2709 0.000 0.000 0.628 0.372 0.000
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#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.4644 0.2883 0.460 0.000 0.528 0.012 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.2068 0.7433 0.904 0.000 0.092 0.004 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.2605 0.7905 0.852 0.000 0.000 0.148 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 5 0.4126 0.2928 0.000 0.000 0.380 0.000 0.620
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 2 0.4453 0.5531 0.048 0.724 0.000 0.228 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.6831 0.2843 0.300 0.268 0.428 0.004 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.2813 0.7886 0.832 0.000 0.000 0.168 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.2377 0.7917 0.872 0.000 0.000 0.128 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.6623 0.3730 0.452 0.000 0.300 0.248 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.5539 0.6255 0.000 0.012 0.152 0.680 0.156
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.4994 0.3896 0.396 0.016 0.576 0.012 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.0000 0.7811 0.000 1.000 0.000 0.000 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 5 0.0290 0.8582 0.000 0.008 0.000 0.000 0.992
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.1628 0.7689 0.000 0.936 0.000 0.056 0.008
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.2304 0.7537 0.000 0.892 0.000 0.100 0.008
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.3857 0.7488 0.688 0.000 0.000 0.312 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.3966 0.7237 0.664 0.000 0.000 0.336 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4687 0.5808 0.000 0.672 0.000 0.288 0.040
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 5 0.1205 0.8288 0.000 0.004 0.000 0.040 0.956
#> 80936433-AA91-4219-98F1-706C36298060 3 0.6402 -0.0218 0.000 0.000 0.472 0.180 0.348
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.4473 0.2416 0.008 0.000 0.412 0.580 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.4341 0.1910 0.592 0.000 0.000 0.004 0.404
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.3534 0.7719 0.744 0.000 0.000 0.256 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 4 0.5470 0.5196 0.000 0.080 0.000 0.588 0.332
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0404 0.7911 0.988 0.000 0.000 0.012 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.5131 0.4418 0.040 0.540 0.000 0.420 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5594 0.4241 0.136 0.000 0.632 0.232 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.4510 0.6789 0.008 0.056 0.000 0.752 0.184
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.5126 0.6635 0.696 0.152 0.000 0.152 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.2648 0.6722 0.000 0.848 0.152 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 2 0.5082 0.4786 0.076 0.664 0.000 0.260 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.3534 0.7716 0.744 0.000 0.000 0.256 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.2329 0.6682 0.124 0.000 0.876 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.6297 0.2842 0.212 0.532 0.000 0.256 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.3366 0.7790 0.768 0.000 0.000 0.232 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0162 0.7894 0.996 0.000 0.000 0.004 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.4203 0.6706 0.016 0.056 0.000 0.796 0.132
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.3210 0.5998 0.000 0.212 0.788 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.4301 0.5418 0.000 0.712 0.000 0.028 0.260
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.5449 0.3778 0.556 0.000 0.376 0.068 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.4637 0.3023 0.452 0.000 0.536 0.012 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0162 0.7373 0.000 0.000 0.996 0.004 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.3774 0.6625 0.008 0.012 0.000 0.780 0.200
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.3039 0.7868 0.808 0.000 0.000 0.192 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.5065 0.5533 0.068 0.692 0.000 0.232 0.008
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.2068 0.6873 0.004 0.000 0.904 0.092 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.3210 0.6247 0.000 0.788 0.000 0.000 0.212
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.4278 0.2337 0.000 0.452 0.000 0.000 0.548
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.4201 0.6735 0.000 0.044 0.000 0.752 0.204
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0290 0.7884 0.992 0.000 0.000 0.008 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0290 0.7884 0.992 0.000 0.000 0.008 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.4981 0.3176 0.440 0.000 0.536 0.012 0.012
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.6765 0.3519 0.400 0.000 0.304 0.296 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323 4 0.6428 0.5210 0.000 0.164 0.012 0.548 0.276
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.3990 0.5061 0.308 0.688 0.000 0.004 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.1892 0.6983 0.000 0.080 0.916 0.004 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0510 0.7921 0.984 0.000 0.000 0.016 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3661 0.7665 0.724 0.000 0.000 0.276 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.3861 0.6242 0.000 0.712 0.000 0.284 0.004
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3816 0.7534 0.696 0.000 0.000 0.304 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.3895 0.7433 0.680 0.000 0.000 0.320 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.6177 0.1934 0.000 0.232 0.000 0.212 0.556
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4402 0.2630 0.636 0.000 0.352 0.012 0.000
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4227 0.1633 0.000 0.000 0.580 0.420 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.3462 0.5957 0.792 0.000 0.196 0.012 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.4817 0.6250 0.000 0.056 0.000 0.680 0.264
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.0693 0.8496 0.000 0.008 0.000 0.012 0.980
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0290 0.7830 0.000 0.992 0.000 0.000 0.008
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.3875 0.6778 0.000 0.048 0.000 0.792 0.160
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4227 0.1633 0.000 0.000 0.580 0.420 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.4620 0.3166 0.320 0.000 0.652 0.028 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0162 0.7373 0.000 0.000 0.996 0.004 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4683 0.5803 0.092 0.732 0.000 0.176 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4520 0.5950 0.000 0.684 0.000 0.284 0.032
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.3774 0.7575 0.704 0.000 0.000 0.296 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.0000 0.8656 0.000 0.000 0.000 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.7903 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0579 0.7856 0.984 0.000 0.000 0.008 0.008
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0566 0.7338 0.012 0.004 0.984 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.6672 0.1332 0.000 0.440 0.000 0.272 0.288
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0963 0.7950 0.964 0.000 0.000 0.036 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3388 0.6661 0.792 0.000 0.200 0.008 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3730 0.7608 0.712 0.000 0.000 0.288 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0290 0.7911 0.992 0.000 0.000 0.008 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4233 0.6717 0.000 0.044 0.000 0.748 0.208
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0510 0.7921 0.984 0.000 0.000 0.016 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 5 0.5830 0.1096 0.000 0.072 0.012 0.364 0.552
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.7383 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.0404 0.8573 0.000 0.012 0.000 0.000 0.988
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0162 0.7909 0.996 0.000 0.000 0.004 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1197 0.7922 0.952 0.000 0.000 0.048 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.6692 0.4213 0.432 0.000 0.272 0.296 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2648 0.7892 0.848 0.000 0.000 0.152 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0806 0.91527 0.000 0.008 0.000 0.020 0.972 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.1138 0.63068 0.000 0.004 0.000 0.960 0.024 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0291 0.75863 0.004 0.000 0.992 0.004 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1219 0.62919 0.000 0.004 0.000 0.948 0.048 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.0000 0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1753 0.72364 0.084 0.000 0.912 0.000 0.000 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.5554 0.22201 0.012 0.392 0.520 0.016 0.000 0.060
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 6 0.3860 0.10260 0.472 0.000 0.000 0.000 0.000 0.528
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#> 4872963F-DEE8-46A2-9173-90EF52BE061E 6 0.3857 0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0146 0.74436 0.004 0.996 0.000 0.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 4 0.4798 0.50493 0.000 0.148 0.032 0.720 0.100 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4384 0.07174 0.520 0.460 0.004 0.000 0.000 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.1951 0.72082 0.016 0.076 0.908 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 6 0.3847 0.12783 0.456 0.000 0.000 0.000 0.000 0.544
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0000 0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.0405 0.53170 0.008 0.000 0.000 0.004 0.000 0.988
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 6 0.3860 0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0291 0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.0000 0.53184 0.000 0.000 0.000 0.000 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 6 0.0260 0.52977 0.008 0.000 0.000 0.000 0.000 0.992
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.5969 0.13412 0.244 0.316 0.000 0.440 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.0458 0.52610 0.000 0.000 0.000 0.016 0.000 0.984
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 6 0.2092 0.44663 0.000 0.000 0.000 0.124 0.000 0.876
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.0146 0.53187 0.004 0.000 0.000 0.000 0.000 0.996
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.7463 -0.09481 0.212 0.196 0.000 0.200 0.392 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.0146 0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.0000 0.53184 0.000 0.000 0.000 0.000 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4462 0.50316 0.712 0.000 0.136 0.000 0.000 0.152
#> 1122039D-5785-4F70-9916-17C585453512 4 0.3867 0.01519 0.000 0.000 0.488 0.512 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 6 0.3857 0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4203 0.51279 0.716 0.000 0.068 0.000 0.000 0.216
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.1152 0.62982 0.000 0.004 0.000 0.952 0.044 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.1387 0.87083 0.000 0.000 0.000 0.068 0.932 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.74484 0.000 1.000 0.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.1636 0.62643 0.000 0.004 0.000 0.936 0.024 0.036
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.3867 0.01519 0.000 0.000 0.488 0.512 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.3874 0.33442 0.000 0.000 0.636 0.008 0.000 0.356
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.3634 0.39095 0.644 0.000 0.000 0.000 0.000 0.356
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0458 0.75600 0.016 0.000 0.984 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.6259 0.21855 0.208 0.436 0.000 0.016 0.000 0.340
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 4 0.5911 0.14509 0.228 0.316 0.000 0.456 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0146 0.53170 0.000 0.000 0.000 0.004 0.000 0.996
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.0000 0.93726 0.000 0.000 0.000 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0291 0.75877 0.004 0.000 0.992 0.004 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 6 0.3860 0.10260 0.472 0.000 0.000 0.000 0.000 0.528
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3911 0.49197 0.712 0.000 0.000 0.000 0.032 0.256
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1531 0.73714 0.068 0.004 0.928 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 4 0.6964 0.22355 0.228 0.252 0.000 0.440 0.080 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3828 0.25619 0.560 0.000 0.000 0.000 0.000 0.440
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5731 0.31435 0.508 0.000 0.204 0.000 0.000 0.288
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.3309 0.27460 0.280 0.000 0.000 0.000 0.000 0.720
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.3847 0.12783 0.456 0.000 0.000 0.000 0.000 0.544
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.1116 0.63144 0.000 0.004 0.000 0.960 0.028 0.008
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 6 0.3955 0.14605 0.436 0.000 0.004 0.000 0.000 0.560
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.4582 0.43104 0.000 0.024 0.032 0.672 0.272 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0260 0.75827 0.000 0.000 0.992 0.008 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.0363 0.92712 0.000 0.012 0.000 0.000 0.988 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 6 0.3857 0.11031 0.468 0.000 0.000 0.000 0.000 0.532
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.3672 0.19962 0.368 0.000 0.000 0.000 0.000 0.632
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.4953 0.16454 0.268 0.000 0.108 0.000 0.000 0.624
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.3266 0.33819 0.272 0.000 0.000 0.000 0.000 0.728
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.299 0.671 0.811 0.4520 0.524 0.524
#> 3 3 0.454 0.749 0.848 0.4033 0.653 0.428
#> 4 4 0.523 0.695 0.824 0.0980 0.948 0.850
#> 5 5 0.558 0.601 0.778 0.0710 0.953 0.849
#> 6 6 0.597 0.550 0.717 0.0657 0.865 0.554
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.9358 0.7203 0.352 0.648
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.2043 0.7110 0.032 0.968
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.0000 0.7857 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.2043 0.6979 0.032 0.968
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.7001 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.7857 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.1633 0.7824 0.976 0.024
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.8608 0.7554 0.284 0.716
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.9460 0.7096 0.364 0.636
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.5946 0.6606 0.856 0.144
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3431 0.7145 0.064 0.936
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.8608 0.7554 0.284 0.716
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1414 0.6999 0.020 0.980
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.8861 0.7487 0.304 0.696
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.9323 0.5675 0.652 0.348
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.9427 0.7131 0.360 0.640
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0000 0.7001 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.8661 0.3647 0.288 0.712
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.7001 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.3733 0.6806 0.072 0.928
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.7674 0.6170 0.776 0.224
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.7001 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 2 0.8608 0.7554 0.284 0.716
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.4022 0.6772 0.080 0.920
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 2 0.2778 0.7152 0.048 0.952
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.4022 0.6772 0.080 0.920
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.7857 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.8499 0.7577 0.276 0.724
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3879 0.7634 0.924 0.076
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 2 0.8608 0.7554 0.284 0.716
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0672 0.7856 0.992 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4022 0.6772 0.080 0.920
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.9491 0.5550 0.632 0.368
#> C06D8112-0FA0-4607-988D-589D8694743F 2 0.8861 0.7487 0.304 0.696
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.8861 0.7487 0.304 0.696
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.2603 0.7131 0.044 0.956
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.9209 0.3425 0.664 0.336
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.2778 0.7728 0.952 0.048
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.9963 0.1279 0.536 0.464
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.7950 0.6006 0.760 0.240
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.8608 0.7554 0.284 0.716
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.9993 -0.2131 0.516 0.484
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.9044 0.7118 0.320 0.680
#> 60EE5A75-84EC-419D-9540-0864A98EA293 2 0.8608 0.7554 0.284 0.716
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.8555 0.7566 0.280 0.720
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.7857 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 1 0.8608 0.5649 0.716 0.284
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.2948 0.7171 0.052 0.948
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 0.9044 0.7382 0.320 0.680
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.7001 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 2 0.8861 0.7487 0.304 0.696
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3879 0.7634 0.924 0.076
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.6148 0.5947 0.152 0.848
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.7883 0.5990 0.764 0.236
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.8499 0.5534 0.724 0.276
#> 311D089C-33F1-4722-9118-F56427C5C128 2 0.8443 0.7587 0.272 0.728
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.9323 0.6813 0.348 0.652
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0672 0.7057 0.008 0.992
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.9460 0.7096 0.364 0.636
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.7001 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.4298 0.7567 0.912 0.088
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.4022 0.6772 0.080 0.920
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.8608 0.7554 0.284 0.716
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 2 0.8608 0.7554 0.284 0.716
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.8713 0.3150 0.708 0.292
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0000 0.7857 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.4298 0.6948 0.088 0.912
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#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.9460 0.7096 0.364 0.636
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 1 0.7950 0.6006 0.760 0.240
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.3114 0.7720 0.944 0.056
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 2 0.9977 0.3681 0.472 0.528
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 2 0.8608 0.7554 0.284 0.716
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.3431 0.7314 0.064 0.936
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.9580 0.0293 0.380 0.620
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.8861 0.7487 0.304 0.696
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.0000 0.7857 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.8713 0.5204 0.708 0.292
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4939 0.6989 0.108 0.892
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.5946 0.6166 0.144 0.856
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.4431 0.7556 0.908 0.092
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.8608 0.7554 0.284 0.716
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.7857 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 2 0.8608 0.7554 0.284 0.716
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.8267 0.5555 0.740 0.260
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.7001 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 2 0.2603 0.7131 0.044 0.956
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.2603 0.7131 0.044 0.956
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.8207 0.5924 0.744 0.256
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.2236 0.7119 0.036 0.964
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 2 0.8207 0.7602 0.256 0.744
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.8207 0.5841 0.744 0.256
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.9460 0.7096 0.364 0.636
#> 1122039D-5785-4F70-9916-17C585453512 1 0.8499 0.5996 0.724 0.276
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 2 0.8713 0.7519 0.292 0.708
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.9248 0.7294 0.340 0.660
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.7001 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.2423 0.7126 0.040 0.960
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.9286 0.5399 0.656 0.344
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.2778 0.7152 0.048 0.952
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.8327 0.5997 0.736 0.264
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.3584 0.7644 0.932 0.068
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 2 0.8608 0.7554 0.284 0.716
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0000 0.7857 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.8909 0.4739 0.692 0.308
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.7001 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 2 0.8608 0.7554 0.284 0.716
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2603 0.7131 0.044 0.956
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.7857 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.8713 0.7490 0.292 0.708
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.8861 0.7487 0.304 0.696
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0000 0.7857 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.7001 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 2 0.8608 0.7554 0.284 0.716
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 2 1.0000 0.3843 0.496 0.504
#> EB7883EB-0079-4548-9132-169E94A698BA 2 0.8608 0.7554 0.284 0.716
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.8763 0.5116 0.704 0.296
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0000 0.7001 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.7745 0.6340 0.772 0.228
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4022 0.6772 0.080 0.920
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.0376 0.7853 0.996 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.4161 0.6796 0.084 0.916
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.8608 0.7554 0.284 0.716
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.8608 0.7554 0.284 0.716
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3274 0.7715 0.940 0.060
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.8608 0.7554 0.284 0.716
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.6482 0.5063 0.680 0.296 0.024
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.5236 0.7509 0.804 0.168 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1163 0.7885 0.028 0.000 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.2031 0.8496 0.016 0.952 0.032
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4413 0.8145 0.124 0.852 0.024
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2959 0.8177 0.100 0.000 0.900
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.3850 0.8169 0.088 0.028 0.884
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.8673 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.6665 0.6937 0.276 0.036 0.688
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3295 0.8169 0.096 0.008 0.896
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.6597 0.5513 0.664 0.312 0.024
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.1399 0.8615 0.968 0.004 0.028
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1620 0.8469 0.012 0.964 0.024
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.2297 0.8573 0.944 0.036 0.020
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.8719 0.3903 0.548 0.128 0.324
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.7169 0.5487 0.404 0.028 0.568
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.6985 0.3943 0.592 0.384 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.3918 0.8000 0.004 0.856 0.140
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.1453 0.8459 0.008 0.968 0.024
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.4873 0.7968 0.152 0.824 0.024
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.1399 0.7589 0.004 0.028 0.968
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0424 0.8499 0.008 0.992 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8673 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.3713 0.8553 0.032 0.892 0.076
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.4121 0.7999 0.868 0.108 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.4475 0.8504 0.072 0.864 0.064
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3295 0.8169 0.096 0.008 0.896
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3502 0.8366 0.896 0.084 0.020
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.6095 0.5971 0.392 0.000 0.608
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1129 0.8640 0.976 0.004 0.020
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4750 0.7880 0.216 0.000 0.784
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4068 0.8193 0.120 0.864 0.016
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.2537 0.8263 0.000 0.920 0.080
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.8673 1.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1129 0.8640 0.976 0.004 0.020
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4994 0.7588 0.816 0.160 0.024
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.6854 0.7755 0.124 0.136 0.740
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.3715 0.8193 0.128 0.004 0.868
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1399 0.8567 0.968 0.028 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.3116 0.7427 0.000 0.108 0.892
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.8673 1.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.6562 0.4480 0.700 0.036 0.264
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.4196 0.8238 0.112 0.864 0.024
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8673 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.1399 0.8619 0.968 0.004 0.028
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.2945 0.8160 0.088 0.004 0.908
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4504 0.5680 0.000 0.196 0.804
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.6229 0.7261 0.764 0.172 0.064
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.6879 0.5232 0.428 0.016 0.556
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0747 0.8530 0.016 0.984 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.1031 0.8626 0.976 0.000 0.024
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4750 0.7880 0.216 0.000 0.784
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2152 0.8495 0.016 0.948 0.036
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.6126 0.5957 0.400 0.000 0.600
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0592 0.8630 0.988 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1636 0.8655 0.964 0.020 0.016
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2878 0.8388 0.000 0.904 0.096
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1399 0.8553 0.028 0.968 0.004
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.7339 0.5621 0.392 0.036 0.572
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0424 0.8499 0.008 0.992 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3686 0.7535 0.860 0.000 0.140
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0747 0.8525 0.016 0.984 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1411 0.8599 0.964 0.036 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0475 0.8679 0.992 0.004 0.004
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.3715 0.8191 0.128 0.004 0.868
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3213 0.8155 0.092 0.008 0.900
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5062 0.7880 0.184 0.800 0.016
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.1129 0.8640 0.976 0.004 0.020
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.4178 0.8132 0.172 0.000 0.828
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0661 0.8662 0.988 0.008 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0592 0.8514 0.012 0.988 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.6375 0.7582 0.244 0.036 0.720
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2998 0.8480 0.016 0.916 0.068
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.2703 0.8508 0.016 0.928 0.056
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.5070 0.7827 0.224 0.004 0.772
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.3619 0.7314 0.000 0.136 0.864
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1289 0.7912 0.032 0.000 0.968
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.7075 -0.1586 0.492 0.488 0.020
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.2584 0.8072 0.064 0.008 0.928
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1585 0.7873 0.028 0.008 0.964
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.7236 0.0458 0.576 0.032 0.392
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.4994 0.7859 0.160 0.816 0.024
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1129 0.8645 0.976 0.004 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.9400 0.1088 0.172 0.424 0.404
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.8673 1.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.4609 0.8112 0.128 0.844 0.028
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.3765 0.8060 0.888 0.084 0.028
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1453 0.7844 0.024 0.008 0.968
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.8673 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.5191 0.8281 0.060 0.828 0.112
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.8673 1.000 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.6264 0.6272 0.380 0.004 0.616
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.2527 0.8533 0.936 0.044 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.4483 0.8104 0.128 0.848 0.024
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.1919 0.8605 0.956 0.024 0.020
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.6126 0.6494 0.268 0.712 0.020
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0747 0.8525 0.016 0.984 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.5860 0.7203 0.228 0.748 0.024
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.3192 0.7414 0.000 0.112 0.888
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1170 0.8537 0.016 0.976 0.008
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.8673 1.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1163 0.8625 0.972 0.028 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.8630 0.4737 0.328 0.552 0.120
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.2998 0.8480 0.016 0.916 0.068
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.3551 0.8172 0.132 0.000 0.868
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.3043 0.8140 0.084 0.008 0.908
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.5981 0.7524 0.080 0.132 0.788
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.6180 0.5663 0.416 0.000 0.584
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.2845 0.8467 0.012 0.920 0.068
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.8673 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.4618 0.7823 0.840 0.136 0.024
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.5356 0.7362 0.784 0.196 0.020
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.4836 0.8240 0.080 0.848 0.072
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.1399 0.8615 0.968 0.004 0.028
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.5277 0.7420 0.796 0.180 0.024
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0592 0.8519 0.012 0.988 0.000
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#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0475 0.8675 0.992 0.004 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.6180 -0.0913 0.584 0.000 0.416
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.6451 0.5258 0.436 0.004 0.560
#> 1122039D-5785-4F70-9916-17C585453512 3 0.2878 0.7465 0.000 0.096 0.904
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6104 0.2335 0.648 0.004 0.348
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1129 0.8640 0.976 0.004 0.020
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.1031 0.8537 0.024 0.976 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.6252 0.6207 0.708 0.268 0.024
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.6908 0.5875 0.036 0.656 0.308
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.5167 0.7482 0.804 0.172 0.024
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.2878 0.7465 0.000 0.096 0.904
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.3295 0.8169 0.096 0.008 0.896
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.8673 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1989 0.8011 0.048 0.004 0.948
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.7319 -0.1292 0.548 0.032 0.420
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1031 0.8537 0.024 0.976 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0237 0.8675 0.996 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.5486 0.7288 0.780 0.196 0.024
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3295 0.8169 0.096 0.008 0.896
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0424 0.8669 0.992 0.000 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1129 0.8640 0.976 0.004 0.020
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3551 0.8188 0.132 0.000 0.868
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0592 0.8514 0.012 0.988 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0747 0.8653 0.984 0.000 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3644 0.7731 0.872 0.004 0.124
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0237 0.8677 0.996 0.004 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.8673 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.7091 0.3185 0.560 0.416 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.2066 0.8399 0.940 0.000 0.060
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2703 0.8508 0.016 0.928 0.056
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1453 0.7844 0.024 0.008 0.968
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2680 0.8451 0.008 0.924 0.068
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0747 0.8653 0.984 0.000 0.016
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.2297 0.8552 0.944 0.036 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5378 0.7873 0.236 0.008 0.756
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0237 0.8677 0.996 0.004 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.8612 0.3042 0.336 0.116 0.092 0.456
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3855 0.7375 0.820 0.012 0.004 0.164
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2861 0.7376 0.000 0.096 0.888 0.016
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.3105 0.7804 0.004 0.856 0.000 0.140
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.5936 0.4444 0.056 0.324 0.000 0.620
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0712 0.7712 0.008 0.004 0.984 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.1211 0.7688 0.000 0.000 0.960 0.040
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1059 0.8334 0.972 0.016 0.000 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.8697 0.4702 0.224 0.072 0.488 0.216
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2266 0.7592 0.000 0.004 0.912 0.084
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.3253 0.7834 0.100 0.008 0.016 0.876
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3854 0.7949 0.844 0.016 0.124 0.016
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 4 0.4800 0.4235 0.004 0.340 0.000 0.656
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.6831 0.0478 0.488 0.016 0.060 0.436
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6497 0.4262 0.596 0.000 0.304 0.100
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5889 0.5847 0.300 0.016 0.652 0.032
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.6921 0.3451 0.580 0.260 0.000 0.160
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 4 0.3037 0.7308 0.000 0.036 0.076 0.888
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.3219 0.7690 0.000 0.836 0.000 0.164
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 4 0.3229 0.7989 0.072 0.048 0.000 0.880
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4488 0.7140 0.000 0.096 0.808 0.096
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3444 0.7528 0.000 0.816 0.000 0.184
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5326 0.3730 0.016 0.604 0.000 0.380
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0817 0.8289 0.976 0.000 0.000 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 4 0.6125 0.1623 0.048 0.436 0.000 0.516
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.2053 0.7613 0.000 0.004 0.924 0.072
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3742 0.8075 0.868 0.016 0.052 0.064
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5369 0.6007 0.296 0.016 0.676 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3798 0.7964 0.848 0.016 0.120 0.016
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.3024 0.7636 0.148 0.000 0.852 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 4 0.3323 0.7924 0.064 0.060 0.000 0.876
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.3249 0.7808 0.000 0.852 0.008 0.140
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2983 0.8196 0.896 0.012 0.076 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3958 0.7957 0.844 0.016 0.116 0.024
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.2593 0.7910 0.892 0.004 0.000 0.104
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.4863 0.7274 0.028 0.108 0.808 0.056
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.1902 0.7796 0.064 0.000 0.932 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.3982 0.6911 0.000 0.004 0.776 0.220
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1247 0.8338 0.968 0.016 0.004 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.5705 0.4621 0.672 0.016 0.284 0.028
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.3006 0.7594 0.012 0.888 0.092 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8317 1.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.2433 0.8313 0.920 0.008 0.060 0.012
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0592 0.7675 0.000 0.000 0.984 0.016
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6167 0.5356 0.000 0.256 0.648 0.096
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3965 0.7640 0.840 0.008 0.032 0.120
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.5994 0.5580 0.320 0.016 0.632 0.032
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 4 0.4889 0.3903 0.004 0.360 0.000 0.636
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2888 0.8062 0.872 0.000 0.124 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.3519 0.7606 0.128 0.016 0.852 0.004
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.3157 0.7789 0.004 0.852 0.000 0.144
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5295 0.6312 0.284 0.016 0.688 0.012
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0707 0.8285 0.980 0.000 0.020 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1631 0.8347 0.956 0.008 0.016 0.020
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0707 0.7983 0.000 0.980 0.000 0.020
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3429 0.7902 0.056 0.876 0.004 0.064
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.5974 0.5858 0.300 0.016 0.648 0.036
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.4925 0.3049 0.000 0.572 0.000 0.428
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.4773 0.7285 0.756 0.016 0.216 0.012
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2831 0.7906 0.004 0.876 0.000 0.120
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0817 0.8299 0.976 0.000 0.000 0.024
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.1975 0.8328 0.944 0.016 0.028 0.012
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.2131 0.7777 0.040 0.016 0.936 0.008
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.2401 0.7545 0.000 0.004 0.904 0.092
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.6353 0.5599 0.072 0.320 0.004 0.604
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2725 0.8240 0.912 0.016 0.056 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.3219 0.7683 0.164 0.000 0.836 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.2773 0.7921 0.004 0.880 0.000 0.116
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.4846 0.7312 0.180 0.016 0.776 0.028
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0779 0.8006 0.004 0.980 0.000 0.016
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.2053 0.8041 0.004 0.924 0.000 0.072
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3949 0.7541 0.140 0.016 0.832 0.012
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.3356 0.7023 0.000 0.000 0.824 0.176
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2088 0.7578 0.004 0.064 0.928 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.9498 -0.0886 0.364 0.280 0.116 0.240
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.2111 0.7596 0.000 0.044 0.932 0.024
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.2909 0.7385 0.000 0.092 0.888 0.020
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.6272 -0.0322 0.512 0.016 0.444 0.028
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 4 0.3687 0.7890 0.080 0.064 0.000 0.856
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.2917 0.8242 0.904 0.016 0.060 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.9434 -0.0831 0.136 0.408 0.200 0.256
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0804 0.8335 0.980 0.012 0.000 0.008
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.2731 0.7624 0.008 0.896 0.092 0.004
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0707 0.8261 0.980 0.000 0.000 0.020
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4010 0.7226 0.000 0.100 0.836 0.064
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0336 0.8317 0.992 0.000 0.000 0.008
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0469 0.7957 0.012 0.988 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.5188 0.6625 0.268 0.016 0.704 0.012
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.2981 0.8243 0.904 0.016 0.048 0.032
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 4 0.2983 0.7970 0.068 0.040 0.000 0.892
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.2643 0.8264 0.916 0.016 0.052 0.016
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 4 0.3367 0.7919 0.092 0.020 0.012 0.876
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2831 0.7906 0.004 0.876 0.000 0.120
#> 31322670-76A2-4308-A71F-D8E00049519D 4 0.3726 0.7784 0.088 0.016 0.032 0.864
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.4126 0.6916 0.004 0.004 0.776 0.216
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.2530 0.7983 0.004 0.896 0.000 0.100
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0707 0.8301 0.980 0.000 0.000 0.020
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.8024 0.2523 0.232 0.536 0.196 0.036
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0779 0.8006 0.004 0.980 0.000 0.016
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.2593 0.7704 0.104 0.000 0.892 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.2466 0.7536 0.000 0.004 0.900 0.096
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.5361 0.7255 0.108 0.000 0.744 0.148
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.5481 0.5916 0.316 0.016 0.656 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0707 0.7985 0.000 0.980 0.000 0.020
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0927 0.8336 0.976 0.016 0.000 0.008
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.3647 0.7026 0.832 0.016 0.000 0.152
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.5520 0.7055 0.768 0.136 0.044 0.052
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1706 0.7962 0.016 0.948 0.036 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.3963 0.7919 0.836 0.016 0.132 0.016
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.5030 0.4263 0.640 0.004 0.004 0.352
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 4 0.4889 0.3901 0.004 0.360 0.000 0.636
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.5215 0.6338 0.712 0.016 0.256 0.016
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0895 0.8011 0.004 0.976 0.000 0.020
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.4387 0.7202 0.236 0.000 0.752 0.012
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.1631 0.8341 0.956 0.016 0.008 0.020
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.5163 -0.3011 0.516 0.000 0.480 0.004
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.3104 0.7743 0.060 0.892 0.044 0.004
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.2960 0.7595 0.020 0.004 0.892 0.084
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 4 0.4464 0.6876 0.024 0.208 0.000 0.768
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#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0779 0.8006 0.004 0.980 0.000 0.016
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2216 0.7794 0.908 0.000 0.092 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.2837 0.8218 0.904 0.016 0.068 0.012
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0524 0.7692 0.004 0.000 0.988 0.008
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.4814 0.6763 0.316 0.000 0.676 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.3300 0.7806 0.008 0.848 0.000 0.144
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1389 0.8160 0.952 0.000 0.000 0.048
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.3123 0.7563 0.844 0.000 0.000 0.156
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1118 0.8205 0.964 0.000 0.036 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.5252 0.5420 0.692 0.020 0.008 0.280
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0336 0.8316 0.992 0.000 0.000 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4933 -0.0940 0.568 0.000 0.432 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.5906 0.5641 0.320 0.016 0.636 0.028
#> 1122039D-5785-4F70-9916-17C585453512 3 0.3668 0.7012 0.000 0.004 0.808 0.188
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.5993 0.0895 0.528 0.016 0.440 0.016
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4058 0.7945 0.840 0.016 0.116 0.028
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.2831 0.7906 0.004 0.876 0.000 0.120
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 4 0.6457 0.1491 0.428 0.044 0.012 0.516
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.4074 0.5732 0.008 0.792 0.196 0.004
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.3360 0.7744 0.860 0.008 0.008 0.124
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.3668 0.7012 0.000 0.004 0.808 0.188
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.2197 0.7589 0.000 0.004 0.916 0.080
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1271 0.8354 0.968 0.012 0.008 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2246 0.7671 0.016 0.052 0.928 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.5604 0.2551 0.476 0.000 0.504 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2831 0.7906 0.004 0.876 0.000 0.120
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0188 0.8315 0.996 0.000 0.000 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.4923 0.5566 0.304 0.004 0.008 0.684
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.2197 0.7589 0.000 0.004 0.916 0.080
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2983 0.8200 0.896 0.016 0.076 0.012
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.6614 0.5952 0.660 0.016 0.116 0.208
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1824 0.7793 0.060 0.000 0.936 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.2831 0.7906 0.004 0.876 0.000 0.120
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1661 0.8325 0.944 0.000 0.052 0.004
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4086 0.7348 0.776 0.000 0.216 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0707 0.8309 0.980 0.000 0.000 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0524 0.8325 0.988 0.000 0.004 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.7086 0.2787 0.548 0.292 0.000 0.160
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3584 0.7895 0.836 0.004 0.152 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2053 0.8036 0.004 0.924 0.000 0.072
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.4488 0.7140 0.000 0.096 0.808 0.096
#> A0C429D9-0638-4873-BFB4-00056AB4719F 4 0.4164 0.6182 0.000 0.264 0.000 0.736
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2911 0.8227 0.900 0.016 0.072 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4097 0.7980 0.840 0.016 0.112 0.032
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.3945 0.7504 0.216 0.000 0.780 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1297 0.8337 0.964 0.016 0.000 0.020
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.7075 0.32610 0.252 0.008 0.112 0.068 0.560
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.5009 0.70144 0.772 0.088 0.008 0.048 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4161 0.20126 0.000 0.000 0.608 0.392 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.2726 0.77517 0.000 0.884 0.000 0.052 0.064
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.4668 0.40379 0.000 0.352 0.000 0.024 0.624
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2648 0.50963 0.000 0.000 0.848 0.152 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.2536 0.48903 0.000 0.004 0.900 0.044 0.052
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3791 0.76360 0.812 0.000 0.076 0.112 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.7337 0.35343 0.192 0.000 0.496 0.252 0.060
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4182 0.25156 0.000 0.000 0.600 0.400 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0510 0.83895 0.000 0.000 0.016 0.000 0.984
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5212 0.70248 0.692 0.000 0.192 0.112 0.004
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.1965 0.79381 0.000 0.096 0.000 0.000 0.904
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.7003 0.36791 0.224 0.000 0.100 0.108 0.568
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6938 0.48317 0.600 0.044 0.240 0.056 0.060
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5947 0.44270 0.232 0.000 0.632 0.116 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.6423 0.42824 0.572 0.296 0.000 0.048 0.084
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0000 0.84360 0.000 0.000 0.000 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2962 0.76619 0.000 0.868 0.000 0.048 0.084
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0162 0.84366 0.000 0.004 0.000 0.000 0.996
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.4074 0.68363 0.000 0.000 0.364 0.636 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3183 0.74630 0.000 0.828 0.000 0.016 0.156
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.78692 1.000 0.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.6285 0.49461 0.000 0.548 0.004 0.176 0.272
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0960 0.78449 0.972 0.000 0.008 0.004 0.016
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.6562 0.14518 0.000 0.308 0.000 0.228 0.464
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3452 0.32749 0.000 0.000 0.756 0.244 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4803 0.74771 0.800 0.036 0.064 0.044 0.056
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5059 0.45461 0.192 0.000 0.696 0.112 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.5080 0.70965 0.708 0.000 0.176 0.112 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.3888 0.53261 0.120 0.000 0.804 0.076 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0404 0.84067 0.000 0.012 0.000 0.000 0.988
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.2747 0.77674 0.000 0.888 0.004 0.048 0.060
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4501 0.73851 0.756 0.000 0.128 0.116 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.5393 0.70371 0.692 0.000 0.176 0.120 0.012
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4004 0.73674 0.832 0.036 0.004 0.052 0.076
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.4371 0.50605 0.052 0.056 0.824 0.040 0.028
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.2187 0.54658 0.056 0.004 0.920 0.008 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0451 0.78573 0.988 0.000 0.008 0.004 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.5986 0.69955 0.000 0.072 0.356 0.552 0.020
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3849 0.76247 0.808 0.000 0.080 0.112 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4776 0.42286 0.612 0.000 0.364 0.004 0.020
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.2576 0.79720 0.008 0.900 0.072 0.012 0.008
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.78692 1.000 0.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.2681 0.78529 0.876 0.004 0.108 0.012 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.2377 0.45075 0.000 0.000 0.872 0.128 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.3264 0.61603 0.000 0.016 0.164 0.820 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5243 0.70897 0.772 0.048 0.040 0.056 0.084
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.5736 0.44549 0.268 0.000 0.632 0.080 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.2690 0.75288 0.000 0.156 0.000 0.000 0.844
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.4487 0.73640 0.756 0.000 0.140 0.104 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.1270 0.55683 0.052 0.000 0.948 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2719 0.77468 0.000 0.884 0.000 0.048 0.068
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5268 0.46235 0.220 0.000 0.668 0.112 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0963 0.78098 0.964 0.000 0.036 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1942 0.79220 0.920 0.000 0.068 0.000 0.012
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2006 0.81208 0.000 0.916 0.000 0.072 0.012
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1741 0.81470 0.040 0.936 0.000 0.024 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.6060 0.43582 0.244 0.000 0.616 0.120 0.020
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.4307 0.05906 0.000 0.504 0.000 0.000 0.496
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.5673 0.61326 0.596 0.000 0.292 0.112 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1124 0.81151 0.000 0.960 0.000 0.036 0.004
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1059 0.78464 0.968 0.000 0.008 0.004 0.020
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4317 0.75255 0.772 0.000 0.116 0.112 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.1278 0.54546 0.020 0.000 0.960 0.016 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.4256 0.61127 0.000 0.000 0.436 0.564 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.2329 0.77918 0.000 0.124 0.000 0.000 0.876
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3617 0.77206 0.824 0.000 0.128 0.044 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.2890 0.51268 0.160 0.000 0.836 0.004 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0162 0.78600 0.996 0.000 0.000 0.004 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0955 0.81350 0.000 0.968 0.000 0.028 0.004
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.3453 0.54994 0.136 0.000 0.832 0.012 0.020
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1608 0.81379 0.000 0.928 0.000 0.072 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.3662 0.71163 0.000 0.744 0.000 0.252 0.004
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3840 0.52950 0.076 0.000 0.808 0.116 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.5839 0.16763 0.000 0.072 0.676 0.192 0.060
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.3561 0.35302 0.000 0.000 0.740 0.260 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.8971 -0.00407 0.296 0.124 0.184 0.048 0.348
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.2852 0.41206 0.000 0.000 0.828 0.172 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.3177 0.37495 0.000 0.000 0.792 0.208 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.6288 -0.02263 0.440 0.000 0.448 0.096 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.3823 0.76377 0.028 0.064 0.000 0.072 0.836
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.4893 0.74111 0.740 0.004 0.140 0.112 0.004
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 4 0.9474 0.09664 0.116 0.264 0.232 0.292 0.096
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1357 0.79222 0.948 0.000 0.048 0.004 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1894 0.79558 0.008 0.920 0.072 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.78692 1.000 0.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4273 0.08790 0.000 0.000 0.552 0.448 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0613 0.78657 0.984 0.000 0.004 0.008 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.2179 0.81301 0.008 0.912 0.008 0.072 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.1341 0.78958 0.944 0.000 0.000 0.056 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.4619 0.50133 0.216 0.000 0.720 0.064 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.3744 0.77915 0.832 0.008 0.120 0.020 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.0000 0.84360 0.000 0.000 0.000 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.2880 0.78122 0.864 0.004 0.120 0.004 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.0000 0.84360 0.000 0.000 0.000 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1124 0.81151 0.000 0.960 0.000 0.036 0.004
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.0794 0.83183 0.000 0.000 0.028 0.000 0.972
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.6288 0.69242 0.004 0.072 0.356 0.540 0.028
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0404 0.81828 0.000 0.988 0.000 0.012 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0579 0.78602 0.984 0.000 0.008 0.008 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0994 0.78488 0.972 0.004 0.004 0.004 0.016
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.7040 0.31198 0.180 0.536 0.248 0.016 0.020
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.3074 0.74271 0.000 0.804 0.000 0.196 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.3460 0.48334 0.128 0.000 0.828 0.044 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.4256 0.61142 0.000 0.000 0.436 0.564 0.000
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#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 3 0.3715 0.45622 0.260 0.000 0.736 0.004 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.2067 0.80799 0.048 0.920 0.032 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.4741 0.72550 0.796 0.056 0.016 0.048 0.084
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.4435 0.22885 0.000 0.016 0.648 0.336 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0609 0.81521 0.000 0.980 0.000 0.020 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.5035 0.38950 0.252 0.000 0.672 0.076 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.4377 0.68215 0.036 0.776 0.168 0.016 0.004
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.5104 0.48337 0.192 0.000 0.692 0.116 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.4138 0.21687 0.000 0.000 0.616 0.384 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0162 0.78600 0.996 0.000 0.000 0.004 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1981 0.79972 0.016 0.920 0.064 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.6833 0.59072 0.656 0.084 0.132 0.048 0.080
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.2482 0.77350 0.892 0.000 0.084 0.024 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.4788 0.50478 0.220 0.008 0.728 0.024 0.020
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.2221 0.81332 0.000 0.036 0.000 0.052 0.912
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.6918 0.18361 0.136 0.480 0.004 0.028 0.352
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.2719 0.69493 0.852 0.000 0.144 0.004 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.3586 0.28394 0.000 0.000 0.736 0.264 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.5053 0.48084 0.044 0.036 0.780 0.096 0.044
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.78692 1.000 0.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1608 0.81379 0.000 0.928 0.000 0.072 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.2196 0.81303 0.004 0.916 0.000 0.024 0.056
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.6384 0.53511 0.624 0.236 0.008 0.048 0.084
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.3508 0.31301 0.000 0.000 0.748 0.252 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.4764 -0.08628 0.548 0.000 0.436 0.004 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.5335 0.69069 0.676 0.000 0.208 0.112 0.004
#> C075F09E-623C-46ED-B927-889B48F450B3 4 0.3586 0.55315 0.000 0.000 0.264 0.736 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.5304 0.70775 0.700 0.000 0.176 0.112 0.012
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.6692 0.40043 0.264 0.000 0.532 0.184 0.020
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4793 0.26865 0.000 0.068 0.700 0.232 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.3048 0.51971 0.176 0.000 0.820 0.004 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.5122 0.69696 0.688 0.000 0.200 0.112 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3791 0.76360 0.812 0.000 0.076 0.112 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1502 0.81211 0.056 0.940 0.004 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.1699 0.81129 0.004 0.944 0.008 0.036 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5647 0.69929 0.676 0.000 0.184 0.120 0.020
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.3816 0.30343 0.000 0.000 0.696 0.304 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.2900 0.77489 0.864 0.000 0.028 0.108 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.1732 0.76681 0.080 0.000 0.000 0.000 0.920
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1608 0.81379 0.000 0.928 0.000 0.072 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2068 0.74603 0.904 0.000 0.092 0.004 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.4498 0.73912 0.756 0.000 0.132 0.112 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2127 0.47018 0.000 0.000 0.892 0.108 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0162 0.78600 0.996 0.000 0.000 0.004 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.4218 0.47138 0.324 0.000 0.668 0.004 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.2515 0.79476 0.008 0.904 0.000 0.044 0.044
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.2338 0.76356 0.916 0.004 0.008 0.048 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.4727 0.71986 0.792 0.076 0.008 0.048 0.076
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1205 0.77810 0.956 0.000 0.040 0.004 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.5594 0.42736 0.604 0.012 0.032 0.016 0.336
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0162 0.78737 0.996 0.000 0.000 0.000 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4390 -0.06860 0.568 0.000 0.428 0.004 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.6625 0.40159 0.268 0.000 0.532 0.184 0.016
#> 1122039D-5785-4F70-9916-17C585453512 4 0.5418 0.70298 0.000 0.068 0.364 0.568 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6145 0.12937 0.448 0.000 0.436 0.112 0.004
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.6010 0.65953 0.632 0.000 0.168 0.184 0.016
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.1124 0.81151 0.000 0.960 0.000 0.036 0.004
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.7749 0.19010 0.440 0.120 0.032 0.052 0.356
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.4918 0.57665 0.008 0.716 0.204 0.072 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4857 0.72521 0.792 0.052 0.024 0.048 0.084
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.5566 0.70350 0.000 0.068 0.364 0.564 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.3480 0.31871 0.000 0.000 0.752 0.248 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2172 0.79134 0.908 0.000 0.076 0.016 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1908 0.49540 0.000 0.000 0.908 0.092 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.5000 0.26324 0.460 0.000 0.516 0.012 0.012
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1124 0.81151 0.000 0.960 0.000 0.036 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0451 0.78580 0.988 0.000 0.008 0.004 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.1671 0.78840 0.076 0.000 0.000 0.000 0.924
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3508 0.31301 0.000 0.000 0.748 0.252 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4541 0.73793 0.752 0.000 0.136 0.112 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.7941 0.31351 0.408 0.000 0.168 0.116 0.308
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3061 0.52318 0.020 0.000 0.844 0.136 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1124 0.81151 0.000 0.960 0.000 0.036 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3639 0.77038 0.824 0.000 0.076 0.100 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5725 0.58752 0.608 0.000 0.280 0.108 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0833 0.78940 0.976 0.000 0.004 0.004 0.016
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2522 0.77715 0.880 0.000 0.012 0.108 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.6512 0.37640 0.548 0.320 0.000 0.048 0.084
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4918 0.70640 0.708 0.000 0.192 0.100 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.1768 0.81871 0.000 0.924 0.000 0.072 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 4 0.3003 0.62393 0.000 0.000 0.188 0.812 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.4444 0.67246 0.000 0.088 0.000 0.156 0.756
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4541 0.73854 0.752 0.000 0.136 0.112 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.3670 0.75799 0.796 0.000 0.180 0.004 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.3333 0.51157 0.208 0.000 0.788 0.004 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1442 0.79267 0.952 0.000 0.032 0.004 0.012
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.4817 0.28266 0.564 0.012 0.000 0.000 0.388 0.036
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.5707 0.47644 0.108 0.024 0.000 0.280 0.004 0.584
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3396 0.46176 0.116 0.000 0.812 0.072 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.5727 0.62708 0.040 0.628 0.000 0.204 0.004 0.124
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.7215 0.20183 0.012 0.280 0.000 0.144 0.452 0.112
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.3789 0.25579 0.416 0.000 0.584 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.3775 0.60202 0.092 0.000 0.780 0.128 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3244 0.48177 0.732 0.000 0.000 0.000 0.000 0.268
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.7197 -0.35820 0.412 0.000 0.364 0.060 0.040 0.124
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.5607 0.10118 0.408 0.000 0.448 0.144 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0000 0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2668 0.60649 0.828 0.000 0.004 0.000 0.000 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.1958 0.81577 0.000 0.100 0.000 0.004 0.896 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4453 0.19893 0.568 0.000 0.000 0.000 0.400 0.032
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.5304 0.46135 0.000 0.000 0.200 0.200 0.000 0.600
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.2593 0.61203 0.844 0.000 0.148 0.000 0.000 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.5915 0.39549 0.032 0.116 0.000 0.280 0.004 0.568
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0000 0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5218 0.64946 0.012 0.656 0.000 0.204 0.004 0.124
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0000 0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.3578 0.76801 0.000 0.000 0.340 0.660 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3874 0.72587 0.000 0.760 0.000 0.000 0.172 0.068
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.2762 0.66383 0.196 0.000 0.000 0.000 0.000 0.804
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.8555 0.32996 0.044 0.392 0.064 0.228 0.196 0.076
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.2003 0.67582 0.116 0.000 0.000 0.000 0.000 0.884
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.7179 0.36627 0.124 0.244 0.040 0.064 0.520 0.008
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3532 0.50371 0.064 0.000 0.796 0.140 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 6 0.5288 0.58647 0.164 0.040 0.000 0.108 0.004 0.684
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4406 0.57202 0.696 0.000 0.224 0.000 0.000 0.080
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2805 0.59759 0.812 0.000 0.004 0.000 0.000 0.184
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.5527 0.55364 0.208 0.000 0.560 0.000 0.000 0.232
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0000 0.88563 0.000 0.000 0.000 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.5254 0.58832 0.000 0.596 0.004 0.280 0.000 0.120
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2491 0.60590 0.836 0.000 0.000 0.000 0.000 0.164
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1910 0.62495 0.892 0.000 0.000 0.000 0.000 0.108
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 6 0.4795 0.55432 0.112 0.012 0.000 0.180 0.000 0.696
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.7035 0.51683 0.108 0.084 0.556 0.060 0.000 0.192
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.4176 0.63107 0.136 0.000 0.768 0.020 0.000 0.076
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2135 0.66909 0.128 0.000 0.000 0.000 0.000 0.872
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.2762 0.78092 0.000 0.000 0.196 0.804 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3198 0.49352 0.740 0.000 0.000 0.000 0.000 0.260
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.6089 0.18217 0.388 0.000 0.324 0.000 0.000 0.288
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1570 0.82589 0.016 0.944 0.000 0.008 0.004 0.028
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.2823 0.66049 0.204 0.000 0.000 0.000 0.000 0.796
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 6 0.3993 0.52436 0.300 0.000 0.024 0.000 0.000 0.676
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1779 0.58476 0.064 0.000 0.920 0.016 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.4223 0.75655 0.076 0.000 0.204 0.720 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.5020 0.51996 0.104 0.012 0.000 0.204 0.004 0.676
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4049 0.36419 0.648 0.000 0.332 0.000 0.000 0.020
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.1863 0.81373 0.000 0.104 0.000 0.000 0.896 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.3615 0.44201 0.700 0.000 0.008 0.000 0.000 0.292
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.3445 0.57100 0.260 0.000 0.732 0.000 0.000 0.008
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.5161 0.61599 0.000 0.620 0.000 0.252 0.004 0.124
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.3175 0.49225 0.744 0.000 0.256 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.3141 0.65723 0.200 0.000 0.012 0.000 0.000 0.788
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.4062 0.54482 0.344 0.004 0.000 0.012 0.000 0.640
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0363 0.81986 0.000 0.988 0.000 0.000 0.012 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.2294 0.81372 0.000 0.892 0.000 0.036 0.000 0.072
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.2841 0.54459 0.824 0.000 0.164 0.000 0.000 0.012
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.3961 0.15052 0.000 0.440 0.000 0.000 0.556 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.4235 0.58740 0.724 0.000 0.084 0.000 0.000 0.192
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#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.4239 0.70883 0.060 0.028 0.056 0.052 0.804 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2883 0.56808 0.788 0.000 0.000 0.000 0.000 0.212
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.3854 -0.16266 0.536 0.000 0.000 0.000 0.000 0.464
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4931 0.51928 0.084 0.000 0.592 0.000 0.000 0.324
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.3371 0.61456 0.292 0.000 0.000 0.000 0.000 0.708
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.346 0.743 0.855 0.4642 0.529 0.529
#> 3 3 0.572 0.730 0.845 0.3832 0.747 0.551
#> 4 4 0.561 0.508 0.728 0.1318 0.884 0.689
#> 5 5 0.527 0.367 0.676 0.0413 0.881 0.643
#> 6 6 0.538 0.334 0.622 0.0487 0.883 0.603
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.6973 0.8073 0.188 0.812
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.8144 0.7414 0.252 0.748
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.4431 0.7858 0.092 0.908
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.7917 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.7056 0.8061 0.192 0.808
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.6343 0.7245 0.160 0.840
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.6048 0.7358 0.148 0.852
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.8433 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.8327 0.7781 0.264 0.736
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.4431 0.7858 0.092 0.908
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.7056 0.8061 0.192 0.808
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.8433 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.7056 0.8061 0.192 0.808
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.9996 -0.2262 0.512 0.488
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.9358 0.3083 0.352 0.648
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.8909 0.4278 0.692 0.308
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.4298 0.8146 0.088 0.912
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.7917 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5059 0.8154 0.112 0.888
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.7056 0.8061 0.192 0.808
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.3431 0.7960 0.064 0.936
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.7056 0.8061 0.192 0.808
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8433 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0376 0.7936 0.004 0.996
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.8433 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.6973 0.8074 0.188 0.812
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.4939 0.7745 0.108 0.892
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.7815 0.7950 0.232 0.768
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.8016 0.6903 0.756 0.244
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.8433 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.7376 0.6598 0.208 0.792
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.7056 0.8061 0.192 0.808
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.7917 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0376 0.8418 0.996 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.6247 0.7077 0.844 0.156
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.7056 0.8061 0.192 0.808
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0376 0.7936 0.004 0.996
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 2 0.5059 0.7717 0.112 0.888
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.8433 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.3431 0.7960 0.064 0.936
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.8433 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2236 0.8238 0.964 0.036
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.7056 0.8061 0.192 0.808
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8433 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.8327 0.6991 0.736 0.264
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.4431 0.7858 0.092 0.908
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.3114 0.7970 0.056 0.944
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.6247 0.8103 0.156 0.844
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.9000 0.4125 0.684 0.316
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.7056 0.8061 0.192 0.808
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.7376 0.7149 0.792 0.208
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.8081 0.6882 0.752 0.248
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.7917 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 1.0000 -0.2428 0.496 0.504
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.7219 0.7186 0.800 0.200
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2603 0.8185 0.956 0.044
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.5059 0.8153 0.112 0.888
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.7056 0.8061 0.192 0.808
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.9661 0.5152 0.392 0.608
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.6973 0.8073 0.188 0.812
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.7219 0.7186 0.800 0.200
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.6712 0.8101 0.176 0.824
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.2423 0.8214 0.960 0.040
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.8433 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 2 0.4431 0.7864 0.092 0.908
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.4431 0.7858 0.092 0.908
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.7056 0.8061 0.192 0.808
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.2603 0.8185 0.956 0.044
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.9580 0.5017 0.620 0.380
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3274 0.8133 0.940 0.060
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.2236 0.8050 0.036 0.964
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.5408 0.7598 0.124 0.876
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.6148 0.8138 0.152 0.848
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.7917 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.5178 0.7700 0.116 0.884
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.3431 0.7960 0.064 0.936
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.4431 0.7858 0.092 0.908
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.9909 0.4653 0.444 0.556
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.4431 0.7858 0.092 0.908
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.3431 0.7960 0.064 0.936
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.9286 0.3430 0.656 0.344
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.7056 0.8061 0.192 0.808
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.2603 0.8185 0.956 0.044
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.8207 0.7838 0.256 0.744
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.8433 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.7056 0.8061 0.192 0.808
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.7219 0.7186 0.800 0.200
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.4431 0.7858 0.092 0.908
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.8433 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.7056 0.8061 0.192 0.808
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.8433 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.8207 0.5381 0.744 0.256
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.7056 0.8061 0.192 0.808
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.7056 0.8061 0.192 0.808
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.8433 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.7056 0.8061 0.192 0.808
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.6887 0.8083 0.184 0.816
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.7056 0.8061 0.192 0.808
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 2 0.4431 0.7864 0.092 0.908
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.7056 0.8061 0.192 0.808
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.1184 0.8364 0.984 0.016
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.8433 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.9775 0.5472 0.412 0.588
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.5629 0.8156 0.132 0.868
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.9881 0.3746 0.564 0.436
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.4431 0.7858 0.092 0.908
#> D09064DF-70AE-4A49-9F70-2A8093C96724 2 0.4431 0.7858 0.092 0.908
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.7299 0.7168 0.796 0.204
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.7056 0.8061 0.192 0.808
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.8433 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.7056 0.8061 0.192 0.808
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.7056 0.8061 0.192 0.808
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.4815 0.8152 0.104 0.896
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.7219 0.7186 0.800 0.200
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.7056 0.8061 0.192 0.808
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.7056 0.8061 0.192 0.808
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0938 0.8384 0.988 0.012
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.5408 0.8155 0.124 0.876
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 2 0.7453 0.6510 0.212 0.788
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.1843 0.8278 0.972 0.028
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.6148 0.7128 0.848 0.152
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.8433 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.7056 0.8061 0.192 0.808
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 2 0.4939 0.7745 0.108 0.892
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.6801 0.8093 0.180 0.820
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 2 0.9522 0.2820 0.372 0.628
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 1.0000 0.2910 0.500 0.500
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.7376 0.6454 0.792 0.208
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.8433 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.3431 0.7960 0.064 0.936
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.0000 0.8433 1.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.7917 0.000 1.000
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#> 5DA6F086-6C3A-43D2-AEA5-E4F56D4761B0 2 0.7056 0.8061 0.192 0.808
#> B0E30CEB-1D96-4028-884A-F6572D4AEB5A 1 0.1843 0.8301 0.972 0.028
#> 7B1BB1C8-CCF1-4CFA-9842-86E692C6AD45 2 0.7056 0.8061 0.192 0.808
#> E1833486-2998-4804-A535-EBF25A992392 2 0.4690 0.7806 0.100 0.900
#> 1469D134-06E6-42EF-9C5A-C30DC2B34C01 2 0.8207 0.7838 0.256 0.744
#> F3F32D39-7ACE-4462-8866-FDCD35DA4599 1 0.3879 0.7946 0.924 0.076
#> E56486B8-FAAE-42BF-B67E-D253783B1043 2 0.3431 0.7960 0.064 0.936
#> F8E9F501-DECA-4A6A-8CF1-1A54915E6FA6 2 0.7056 0.8061 0.192 0.808
#> B3AFCDBB-95EF-4028-84F7-9DBC39B25E70 2 0.3431 0.7960 0.064 0.936
#> 864ACE9F-29B4-4BB2-A966-E6F601637A79 2 0.8327 0.7781 0.264 0.736
#> 932BAFF1-A2A8-404F-A9E9-44DCAA8CFF83 1 0.0000 0.8433 1.000 0.000
#> 1C82688E-01A7-4723-8266-F614FB7EABE5 1 0.0000 0.8433 1.000 0.000
#> 8FED16FD-AFBF-475D-A19F-1BC84D0AA571 2 0.4431 0.7858 0.092 0.908
#> 9EF7685F-CA09-4869-94EA-12A1129093B1 2 0.3431 0.7960 0.064 0.936
#> 18AB08E8-6C1A-49E4-9DF0-79D80D9BEC78 2 0.4431 0.7858 0.092 0.908
#> 97FB3176-395F-475B-8EAE-332C5BEE8155 1 0.0000 0.8433 1.000 0.000
#> E1876307-DFD9-4688-876F-D71B37466068 2 0.7056 0.8061 0.192 0.808
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04 2 0.1843 0.7966 0.028 0.972
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00 2 0.4161 0.7893 0.084 0.916
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79 2 0.3431 0.7960 0.064 0.936
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 2 0.8608 0.7693 0.284 0.716
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 1 0.3114 0.8129 0.944 0.056
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 2 0.4431 0.7858 0.092 0.908
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 2 0.4431 0.7858 0.092 0.908
#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.7219 0.7186 0.800 0.200
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 1 0.9209 0.3664 0.664 0.336
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 2 0.4431 0.7858 0.092 0.908
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.7056 0.8061 0.192 0.808
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.7883 0.6968 0.764 0.236
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.6623 0.8110 0.172 0.828
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.7917 0.000 1.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.7056 0.8061 0.192 0.808
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.9129 0.3865 0.672 0.328
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.7917 0.000 1.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.0000 0.8433 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 2 0.4431 0.7858 0.092 0.908
#> 985FEEC2-9737-4018-80DF-21A07AB47900 2 0.9922 -0.0621 0.448 0.552
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.8016 0.6903 0.756 0.244
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.0000 0.8433 1.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.7056 0.8061 0.192 0.808
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.7917 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 2 0.9754 0.5570 0.408 0.592
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.7056 0.8061 0.192 0.808
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.9248 0.6863 0.340 0.660
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0000 0.8433 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.7056 0.8061 0.192 0.808
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.8433 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 2 0.4431 0.7858 0.092 0.908
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.7219 0.7186 0.800 0.200
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.7056 0.8061 0.192 0.808
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.9608 0.1589 0.616 0.384
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.8433 1.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.3431 0.7960 0.064 0.936
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.0000 0.7917 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.7056 0.8061 0.192 0.808
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.7056 0.8061 0.192 0.808
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 2 0.9963 0.4289 0.464 0.536
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.8267 0.7814 0.260 0.740
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.7056 0.8061 0.192 0.808
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.7056 0.8061 0.192 0.808
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.8861 0.7344 0.304 0.696
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.7056 0.8061 0.192 0.808
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.8433 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.8433 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.0000 0.8433 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.1633 0.8294 0.976 0.024
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.4431 0.7858 0.092 0.908
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.7056 0.8061 0.192 0.808
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.7056 0.8061 0.192 0.808
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.5842 0.8148 0.140 0.860
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.7917 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 2 0.7950 0.5985 0.240 0.760
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.4161 0.7930 0.916 0.084
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.8433 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.6887 0.7317 0.816 0.184
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.7917 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.6148 0.7555 0.848 0.152
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.8433 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.1843 0.8285 0.972 0.028
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.6887 0.6825 0.816 0.184
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.8433 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.4431 0.7858 0.092 0.908
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.7528 0.6448 0.216 0.784
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.5519 0.8144 0.128 0.872
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.9580 0.6012 0.620 0.380
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.8433 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.2948 0.7973 0.052 0.948
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.8443 0.5280 0.728 0.272
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0376 0.8418 0.996 0.004
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.7376 0.6566 0.208 0.792
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.9044 0.4115 0.680 0.320
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.8433 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.4815 0.7759 0.896 0.104
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.7745 0.7027 0.772 0.228
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.7056 0.8061 0.192 0.808
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.9988 0.3947 0.480 0.520
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.3431 0.7960 0.064 0.936
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.7056 0.8061 0.192 0.808
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.8555 0.6556 0.720 0.280
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.8207 0.7841 0.256 0.744
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.9970 -0.1412 0.468 0.532
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.4431 0.7858 0.092 0.908
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.8433 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.7056 0.8061 0.192 0.808
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.3431 0.7960 0.064 0.936
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.7219 0.7186 0.800 0.200
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.8661 0.7555 0.288 0.712
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.6623 0.8109 0.172 0.828
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.7056 0.8061 0.192 0.808
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.7453 0.7128 0.788 0.212
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 2 0.4939 0.7745 0.108 0.892
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 2 0.4431 0.7858 0.092 0.908
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.8433 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.7056 0.8061 0.192 0.808
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.7056 0.8061 0.192 0.808
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.4431 0.8159 0.092 0.908
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.4939 0.7745 0.108 0.892
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.8433 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.7219 0.7186 0.800 0.200
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.4431 0.7858 0.092 0.908
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.8433 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.8267 0.7731 0.260 0.740
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.3733 0.7937 0.072 0.928
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.9881 0.4228 0.564 0.436
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.7219 0.7186 0.800 0.200
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.8433 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.7056 0.8061 0.192 0.808
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.8207 0.7838 0.256 0.744
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.9286 0.3429 0.656 0.344
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.3431 0.7960 0.064 0.936
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.8433 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.7056 0.8061 0.192 0.808
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.7056 0.8061 0.192 0.808
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.7219 0.7186 0.800 0.200
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.8433 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.4939 0.7745 0.108 0.892
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.8433 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.8433 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.7056 0.8061 0.192 0.808
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.2778 0.8153 0.952 0.048
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.9963 0.4698 0.464 0.536
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.7453 0.7128 0.788 0.212
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.7056 0.8061 0.192 0.808
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.8433 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.8433 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.8661 0.4654 0.712 0.288
#> 1122039D-5785-4F70-9916-17C585453512 2 0.4431 0.7858 0.092 0.908
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.8433 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.8144 0.5471 0.748 0.252
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.2423 0.8060 0.040 0.960
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.7056 0.8061 0.192 0.808
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.8207 0.7838 0.256 0.744
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.8016 0.7909 0.244 0.756
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.4298 0.7876 0.088 0.912
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 2 0.7815 0.6172 0.232 0.768
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.8433 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.4431 0.7858 0.092 0.908
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.9170 0.3784 0.668 0.332
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.6973 0.8073 0.188 0.812
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.8433 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.7056 0.8061 0.192 0.808
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.4939 0.7745 0.108 0.892
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.8433 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.5294 0.7552 0.880 0.120
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.4431 0.7858 0.092 0.908
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3879 0.8128 0.076 0.924
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.8433 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.8813 0.6377 0.700 0.300
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.8016 0.5633 0.756 0.244
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.8433 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.4431 0.8142 0.092 0.908
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.7376 0.7149 0.792 0.208
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0376 0.7936 0.004 0.996
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.4431 0.7858 0.092 0.908
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.7056 0.8061 0.192 0.808
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.8433 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.8433 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 2 1.0000 -0.2503 0.500 0.500
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.8433 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.1643 0.89830 0.000 0.956 0.044
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.3713 0.85322 0.032 0.892 0.076
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1860 0.78793 0.052 0.000 0.948
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.6225 0.33025 0.000 0.432 0.568
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#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0424 0.90170 0.000 0.992 0.008
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 3 0.6045 0.42388 0.000 0.380 0.620
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.3112 0.87064 0.004 0.900 0.096
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.5331 0.81609 0.824 0.100 0.076
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.5845 0.58551 0.004 0.688 0.308
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.2711 0.84496 0.912 0.088 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.5223 0.69979 0.176 0.024 0.800
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.6244 0.30921 0.440 0.000 0.560
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.3412 0.72542 0.876 0.000 0.124
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.3528 0.84225 0.892 0.092 0.016
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0237 0.90295 0.000 0.996 0.004
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 3 0.6062 0.43026 0.000 0.384 0.616
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.7616 0.59385 0.636 0.292 0.072
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.0237 0.90295 0.000 0.996 0.004
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 1 0.8699 0.36669 0.512 0.112 0.376
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.4092 0.83174 0.876 0.088 0.036
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0237 0.90295 0.000 0.996 0.004
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.2537 0.84433 0.920 0.080 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.2448 0.78612 0.076 0.000 0.924
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.3267 0.73019 0.884 0.000 0.116
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0237 0.90295 0.000 0.996 0.004
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.5346 0.80887 0.824 0.088 0.088
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.2860 0.84520 0.912 0.084 0.004
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.1989 0.78820 0.048 0.004 0.948
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 3 0.6180 0.35908 0.000 0.416 0.584
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0237 0.90295 0.000 0.996 0.004
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.1529 0.89891 0.000 0.960 0.040
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.8208 -0.07955 0.452 0.072 0.476
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.3461 0.86498 0.024 0.900 0.076
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0424 0.90300 0.000 0.992 0.008
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0592 0.90295 0.000 0.988 0.012
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.2261 0.88804 0.000 0.932 0.068
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.1860 0.89614 0.000 0.948 0.052
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.2711 0.84496 0.912 0.088 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.2711 0.84496 0.912 0.088 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.3805 0.83953 0.884 0.092 0.024
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.4689 0.82558 0.852 0.096 0.052
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.1989 0.78820 0.048 0.004 0.948
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0592 0.90311 0.000 0.988 0.012
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.2165 0.89056 0.000 0.936 0.064
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.1411 0.88150 0.000 0.964 0.036
#> 80936433-AA91-4219-98F1-706C36298060 3 0.6079 0.42241 0.000 0.388 0.612
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 3 0.7310 0.47425 0.324 0.048 0.628
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.6632 0.72529 0.732 0.204 0.064
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.1860 0.83328 0.948 0.052 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.3500 0.73344 0.880 0.004 0.116
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.6215 0.34063 0.000 0.428 0.572
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.3267 0.73019 0.884 0.000 0.116
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.2711 0.84496 0.912 0.088 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.4609 0.82745 0.856 0.092 0.052
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.7980 0.43994 0.572 0.356 0.072
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.3129 0.84497 0.904 0.088 0.008
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.2448 0.78612 0.076 0.000 0.924
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5291 0.64223 0.268 0.000 0.732
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.5115 0.73206 0.016 0.796 0.188
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.8894 0.37987 0.572 0.236 0.192
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.2711 0.84496 0.912 0.088 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.5982 0.45013 0.004 0.328 0.668
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.7400 0.64351 0.664 0.264 0.072
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.2625 0.84496 0.916 0.084 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.5785 0.54720 0.332 0.000 0.668
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.8273 0.14728 0.476 0.448 0.076
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.3377 0.84398 0.896 0.092 0.012
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.5212 0.81592 0.828 0.108 0.064
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.3267 0.73019 0.884 0.000 0.116
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.1753 0.89724 0.000 0.952 0.048
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.4475 0.82608 0.072 0.864 0.064
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.1129 0.77162 0.004 0.020 0.976
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0424 0.90300 0.000 0.992 0.008
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4555 0.62329 0.800 0.000 0.200
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.6351 0.68809 0.168 0.760 0.072
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.6274 0.05168 0.544 0.000 0.456
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.1860 0.78793 0.052 0.000 0.948
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.2711 0.84496 0.912 0.088 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1860 0.89614 0.000 0.948 0.052
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.8371 0.52356 0.116 0.292 0.592
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.3500 0.73344 0.880 0.004 0.116
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.8100 0.32862 0.512 0.420 0.068
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0424 0.90170 0.000 0.992 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0237 0.90295 0.000 0.996 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.3267 0.73019 0.884 0.000 0.116
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2448 0.78612 0.076 0.000 0.924
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.4796 0.71780 0.220 0.000 0.780
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.2711 0.84496 0.912 0.088 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0237 0.90295 0.000 0.996 0.004
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0237 0.90295 0.000 0.996 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.3267 0.82352 0.000 0.884 0.116
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.2448 0.78612 0.076 0.000 0.924
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.3528 0.84225 0.892 0.092 0.016
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.3267 0.73019 0.884 0.000 0.116
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.2448 0.78612 0.076 0.000 0.924
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.3722 0.84159 0.888 0.088 0.024
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.8518 0.15882 0.356 0.104 0.540
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.1989 0.78820 0.048 0.004 0.948
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.6126 0.21092 0.600 0.000 0.400
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.3267 0.73019 0.884 0.000 0.116
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3445 0.84123 0.896 0.088 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1753 0.89724 0.000 0.952 0.048
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.4326 0.79162 0.012 0.844 0.144
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.5875 0.78964 0.792 0.136 0.072
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.3112 0.73377 0.004 0.096 0.900
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.3445 0.84126 0.896 0.088 0.016
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0237 0.90295 0.000 0.996 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1643 0.89830 0.000 0.956 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3500 0.73344 0.880 0.004 0.116
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.2356 0.84203 0.928 0.072 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3551 0.76658 0.132 0.000 0.868
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2625 0.84494 0.916 0.084 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.2625 0.84496 0.916 0.084 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.1753 0.89724 0.000 0.952 0.048
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.4654 0.75624 0.792 0.208 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.8063 -0.03781 0.448 0.488 0.064
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3267 0.73019 0.884 0.000 0.116
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0237 0.90301 0.000 0.996 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.2711 0.84496 0.912 0.088 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.80031 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6313 0.43916 0.676 0.016 0.308
#> 1122039D-5785-4F70-9916-17C585453512 3 0.1989 0.78844 0.048 0.004 0.948
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.2711 0.84496 0.912 0.088 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4931 0.73893 0.828 0.032 0.140
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.4399 0.70271 0.000 0.812 0.188
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0424 0.90300 0.000 0.992 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5371 0.79368 0.048 0.812 0.140
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.9211 0.22694 0.312 0.512 0.176
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.1989 0.78844 0.048 0.004 0.948
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5138 0.65881 0.252 0.000 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2625 0.84494 0.916 0.084 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3619 0.76466 0.136 0.000 0.864
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5229 0.81540 0.828 0.104 0.068
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0592 0.90295 0.000 0.988 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2711 0.84496 0.912 0.088 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0237 0.90295 0.000 0.996 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.2448 0.78612 0.076 0.000 0.924
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2356 0.84202 0.928 0.072 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3722 0.84039 0.888 0.088 0.024
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.3784 0.76633 0.132 0.004 0.864
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1860 0.86560 0.000 0.948 0.052
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.2711 0.84496 0.912 0.088 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4178 0.67230 0.828 0.000 0.172
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3850 0.83971 0.884 0.088 0.028
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2711 0.84496 0.912 0.088 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.1753 0.87809 0.000 0.952 0.048
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3267 0.73019 0.884 0.000 0.116
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6215 0.33926 0.000 0.428 0.572
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1860 0.78793 0.052 0.000 0.948
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0237 0.90295 0.000 0.996 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1529 0.82682 0.960 0.040 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.2711 0.84496 0.912 0.088 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5016 0.59165 0.760 0.000 0.240
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4206 0.82930 0.872 0.088 0.040
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.6005 0.70839 0.000 0.616 0.060 0.324
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.5968 0.65363 0.048 0.624 0.004 0.324
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4941 0.32137 0.000 0.000 0.564 0.436
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5292 0.36220 0.000 0.480 0.008 0.512
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2408 0.73925 0.000 0.896 0.000 0.104
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.6567 0.21386 0.308 0.000 0.588 0.104
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 4 0.7921 -0.14551 0.328 0.000 0.324 0.348
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.7259 0.23076 0.208 0.124 0.628 0.040
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4776 0.38295 0.000 0.000 0.624 0.376
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.71416 0.000 1.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0657 0.78375 0.984 0.004 0.012 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.71416 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.9516 0.09938 0.396 0.196 0.148 0.260
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.7868 0.01889 0.360 0.024 0.144 0.472
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.8294 0.53237 0.560 0.104 0.208 0.128
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.5154 0.68881 0.012 0.660 0.004 0.324
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 4 0.5292 0.36197 0.000 0.480 0.008 0.512
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.71416 0.000 1.000 0.000 0.000
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#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.4898 0.67458 0.780 0.000 0.116 0.104
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 1 0.7525 0.40154 0.564 0.060 0.072 0.304
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 3 0.4994 0.25064 0.000 0.000 0.520 0.480
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.4790 0.71262 0.000 0.620 0.000 0.380
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.4989 0.40500 0.528 0.000 0.472 0.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 4 0.4609 0.39499 0.000 0.224 0.024 0.752
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.7143 0.58579 0.000 0.484 0.136 0.380
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.7527 0.42535 0.484 0.012 0.368 0.136
#> 4326E7CF-426E-4352-9903-27BF06E76626 4 0.6895 -0.15125 0.000 0.276 0.148 0.576
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.1593 0.78084 0.956 0.016 0.024 0.004
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.5961 0.36942 0.004 0.064 0.660 0.272
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.3172 0.36103 0.160 0.000 0.840 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.4981 0.41563 0.536 0.000 0.464 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.2275 0.77049 0.928 0.020 0.048 0.004
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 4 0.5376 0.35351 0.000 0.396 0.016 0.588
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.8362 0.42096 0.544 0.100 0.124 0.232
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.0000 0.71416 0.000 1.000 0.000 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.8314 0.15612 0.240 0.140 0.540 0.080
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0564 0.78439 0.988 0.004 0.004 0.004
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.4776 0.38295 0.000 0.000 0.624 0.376
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.4776 0.50075 0.624 0.000 0.376 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.71416 0.000 1.000 0.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.5438 0.22293 0.536 0.008 0.452 0.004
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0188 0.78389 0.996 0.000 0.004 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.4925 0.32930 0.000 0.000 0.572 0.428
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.4722 0.39943 0.000 0.300 0.008 0.692
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.4500 0.73793 0.000 0.684 0.000 0.316
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.1624 0.41633 0.020 0.000 0.952 0.028
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.6932 0.60280 0.004 0.496 0.096 0.404
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.3649 0.74600 0.000 0.796 0.000 0.204
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.4164 0.74540 0.000 0.736 0.000 0.264
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.6486 0.64251 0.004 0.536 0.064 0.396
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.4804 0.71533 0.000 0.616 0.000 0.384
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.1902 0.76935 0.932 0.004 0.064 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.2718 0.76825 0.912 0.020 0.056 0.012
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.3487 0.74377 0.872 0.020 0.016 0.092
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.4925 0.32930 0.000 0.000 0.572 0.428
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.3764 0.74550 0.000 0.784 0.000 0.216
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.6617 0.63367 0.000 0.532 0.088 0.380
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.2149 0.64407 0.000 0.912 0.000 0.088
#> 80936433-AA91-4219-98F1-706C36298060 4 0.5279 0.35654 0.000 0.400 0.012 0.588
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.6944 0.12103 0.284 0.040 0.064 0.612
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.7097 0.46078 0.604 0.032 0.088 0.276
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.3569 0.67967 0.804 0.000 0.196 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 4 0.5273 0.36424 0.000 0.456 0.008 0.536
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.3801 0.66333 0.780 0.000 0.220 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.2586 0.76188 0.912 0.008 0.012 0.068
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.7738 0.29664 0.500 0.060 0.072 0.368
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0804 0.78368 0.980 0.008 0.012 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.4898 0.34794 0.000 0.000 0.584 0.416
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0804 0.41711 0.008 0.000 0.980 0.012
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.5696 0.61193 0.024 0.592 0.004 0.380
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.8555 -0.16153 0.336 0.028 0.264 0.372
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0188 0.78360 0.996 0.004 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 4 0.5055 0.22546 0.000 0.032 0.256 0.712
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.7463 0.36419 0.536 0.036 0.088 0.340
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.1302 0.78178 0.956 0.000 0.044 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.3355 0.35694 0.160 0.000 0.836 0.004
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.8333 0.20060 0.444 0.080 0.096 0.380
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.3970 0.73176 0.836 0.036 0.124 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.6907 0.48609 0.620 0.028 0.084 0.268
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.4948 0.43822 0.560 0.000 0.440 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.4790 0.71262 0.000 0.620 0.000 0.380
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.7034 0.66905 0.088 0.624 0.036 0.252
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.6109 0.27873 0.016 0.020 0.504 0.460
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.3873 0.74561 0.000 0.772 0.000 0.228
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4955 0.43681 0.556 0.000 0.444 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.7796 0.54483 0.024 0.464 0.132 0.380
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.3157 0.36822 0.144 0.000 0.852 0.004
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.4989 0.26692 0.000 0.000 0.528 0.472
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0895 0.78292 0.976 0.004 0.020 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.4790 0.71262 0.000 0.620 0.000 0.380
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.5364 0.38950 0.052 0.192 0.012 0.744
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4454 0.58944 0.692 0.000 0.308 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.9630 0.24773 0.256 0.348 0.132 0.264
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.3764 0.74660 0.000 0.784 0.000 0.216
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4888 0.47128 0.588 0.000 0.412 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4950 0.38387 0.004 0.000 0.620 0.376
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.4562 0.42592 0.028 0.000 0.764 0.208
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0804 0.78387 0.980 0.008 0.012 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0188 0.71580 0.000 0.996 0.000 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.5443 0.64007 0.016 0.616 0.004 0.364
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4776 0.38295 0.000 0.000 0.624 0.376
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.2667 0.76703 0.912 0.020 0.060 0.008
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4661 0.55799 0.652 0.000 0.348 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4817 0.37352 0.000 0.000 0.612 0.388
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0992 0.78385 0.976 0.004 0.012 0.008
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.6610 0.21651 0.016 0.196 0.664 0.124
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4996 0.24609 0.000 0.000 0.516 0.484
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.4804 -0.10002 0.384 0.000 0.616 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4522 0.57690 0.680 0.000 0.320 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0188 0.78360 0.996 0.004 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.4790 0.71262 0.000 0.620 0.000 0.380
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.4579 0.74264 0.004 0.756 0.016 0.224
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.8622 0.38296 0.500 0.076 0.180 0.244
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.6274 0.21571 0.020 0.024 0.520 0.436
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0188 0.78360 0.996 0.004 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0524 0.71163 0.004 0.988 0.000 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.4643 0.72908 0.000 0.656 0.000 0.344
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.4730 0.51897 0.636 0.000 0.364 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0188 0.78389 0.996 0.000 0.004 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.5093 0.39899 0.012 0.000 0.640 0.348
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1902 0.77411 0.932 0.004 0.064 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.4661 0.72772 0.000 0.652 0.000 0.348
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3702 0.73669 0.860 0.028 0.100 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.8327 0.17677 0.452 0.364 0.124 0.060
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4817 0.48685 0.612 0.000 0.388 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.4164 0.74614 0.000 0.736 0.000 0.264
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0524 0.78398 0.988 0.008 0.004 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4454 0.59286 0.692 0.000 0.308 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5000 0.19215 0.504 0.000 0.496 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.5039 -0.01680 0.000 0.004 0.404 0.592
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0657 0.78375 0.984 0.004 0.012 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4761 0.41811 0.628 0.000 0.372 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.3801 0.42008 0.000 0.780 0.000 0.220
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.3649 0.74600 0.000 0.796 0.000 0.204
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7900 0.52813 0.024 0.452 0.144 0.380
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.9027 0.43008 0.148 0.484 0.152 0.216
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.5161 -0.00853 0.000 0.008 0.400 0.592
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.7699 0.23526 0.220 0.000 0.400 0.380
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4012 0.43220 0.016 0.000 0.800 0.184
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5128 0.69514 0.788 0.032 0.048 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4250 0.74458 0.000 0.724 0.000 0.276
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0188 0.78360 0.996 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.3356 0.74726 0.000 0.824 0.000 0.176
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4776 0.38295 0.000 0.000 0.624 0.376
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.78351 1.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4173 0.65784 0.804 0.004 0.172 0.020
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.5291 0.36958 0.024 0.000 0.652 0.324
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1940 0.73379 0.000 0.924 0.000 0.076
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0188 0.78360 0.996 0.004 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.4925 -0.21494 0.428 0.000 0.572 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4819 0.43525 0.652 0.004 0.344 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0336 0.78354 0.992 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.4431 0.70317 0.000 0.696 0.000 0.304
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4804 0.48778 0.616 0.000 0.384 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5296 -0.34046 0.000 0.500 0.008 0.492
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.5000 0.21870 0.000 0.000 0.504 0.496
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0336 0.71350 0.000 0.992 0.000 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2704 0.73350 0.876 0.000 0.124 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1593 0.78069 0.956 0.016 0.024 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.3873 0.32128 0.228 0.000 0.772 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1229 0.78188 0.968 0.004 0.008 0.020
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3771 0.527144 0.000 0.796 0.000 0.164 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.7657 -0.019303 0.024 0.404 0.028 0.364 0.180
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0579 0.665633 0.000 0.000 0.984 0.008 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4164 0.445620 0.000 0.024 0.200 0.764 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4235 0.313315 0.000 0.656 0.000 0.336 0.008
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#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4437 -0.383931 0.532 0.000 0.000 0.004 0.464
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.1892 0.562340 0.000 0.916 0.000 0.080 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.1952 0.603341 0.912 0.000 0.000 0.004 0.084
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4707 -0.259460 0.588 0.000 0.000 0.020 0.392
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.7340 -0.230449 0.424 0.000 0.256 0.032 0.288
#> 1122039D-5785-4F70-9916-17C585453512 3 0.5008 0.541128 0.004 0.004 0.696 0.236 0.060
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.2570 0.574409 0.888 0.000 0.000 0.028 0.084
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.6943 0.166037 0.516 0.000 0.188 0.032 0.264
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.4693 0.332721 0.000 0.244 0.056 0.700 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.4800 0.434697 0.000 0.716 0.000 0.196 0.088
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7792 0.255528 0.120 0.576 0.060 0.128 0.116
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.8709 0.138522 0.132 0.412 0.052 0.124 0.280
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.5008 0.541128 0.004 0.004 0.696 0.236 0.060
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5474 0.395942 0.188 0.000 0.668 0.004 0.140
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2260 0.597870 0.908 0.000 0.000 0.028 0.064
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4705 0.507278 0.052 0.000 0.724 0.008 0.216
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4530 0.522046 0.764 0.080 0.000 0.008 0.148
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2011 0.565506 0.000 0.908 0.000 0.088 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.1544 0.601018 0.932 0.000 0.000 0.000 0.068
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4067 0.363309 0.000 0.692 0.000 0.300 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3301 0.614635 0.072 0.000 0.848 0.000 0.080
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2067 0.590783 0.920 0.000 0.000 0.032 0.048
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.5574 0.479115 0.672 0.004 0.048 0.036 0.240
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.6103 0.406571 0.160 0.020 0.652 0.008 0.160
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4192 0.270338 0.000 0.596 0.000 0.404 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1341 0.606158 0.944 0.000 0.000 0.000 0.056
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.5018 0.611626 0.268 0.000 0.068 0.000 0.664
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.5895 0.377354 0.624 0.000 0.148 0.008 0.220
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2139 0.597399 0.916 0.000 0.000 0.032 0.052
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.5778 0.039561 0.000 0.460 0.000 0.452 0.088
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4562 -0.426317 0.548 0.000 0.004 0.004 0.444
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.4215 0.468732 0.000 0.052 0.172 0.772 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2580 0.653541 0.000 0.000 0.892 0.064 0.044
#> A0C429D9-0638-4873-BFB4-00056AB4719F 4 0.4448 -0.040806 0.000 0.480 0.000 0.516 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3278 0.467021 0.824 0.000 0.000 0.020 0.156
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1952 0.592459 0.912 0.000 0.000 0.004 0.084
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 5 0.6438 0.623830 0.232 0.000 0.196 0.012 0.560
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1626 0.606938 0.940 0.016 0.000 0.000 0.044
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3479 2.86e-01 0.008 0.768 0.000 0.012 0.212 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.6709 1.58e-01 0.008 0.328 0.008 0.380 0.268 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1078 5.92e-01 0.012 0.008 0.964 0.016 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 5 0.6270 -1.09e-01 0.008 0.076 0.060 0.376 0.480 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.3279 4.36e-01 0.000 0.176 0.000 0.028 0.796 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.5918 4.87e-01 0.496 0.004 0.276 0.000 0.000 0.224
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.7934 -1.12e-01 0.244 0.080 0.384 0.060 0.000 0.232
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 6 0.1887 5.93e-01 0.048 0.012 0.000 0.016 0.000 0.924
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.8881 1.73e-01 0.172 0.200 0.364 0.092 0.028 0.144
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1788 6.03e-01 0.076 0.000 0.916 0.004 0.000 0.004
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.2655 4.88e-01 0.004 0.140 0.000 0.008 0.848 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 6 0.2968 6.03e-01 0.056 0.032 0.000 0.044 0.000 0.868
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.0405 5.58e-01 0.004 0.008 0.000 0.000 0.988 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 4 0.8700 -7.21e-02 0.104 0.260 0.024 0.296 0.064 0.252
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.8860 6.53e-02 0.168 0.112 0.216 0.280 0.004 0.220
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 6 0.7828 1.99e-01 0.220 0.264 0.000 0.116 0.028 0.372
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.6346 9.34e-02 0.004 0.336 0.004 0.368 0.288 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.6171 -1.80e-01 0.008 0.012 0.184 0.288 0.508 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.3487 5.25e-01 0.000 0.168 0.000 0.044 0.788 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0405 5.61e-01 0.004 0.008 0.000 0.000 0.988 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4389 2.93e-01 0.032 0.000 0.596 0.372 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.3731 3.32e-01 0.004 0.240 0.000 0.020 0.736 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.1692 5.90e-01 0.048 0.012 0.000 0.008 0.000 0.932
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.4094 4.93e-01 0.004 0.252 0.000 0.036 0.708 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.4778 5.88e-01 0.076 0.080 0.000 0.104 0.000 0.740
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.4330 4.75e-01 0.008 0.232 0.000 0.052 0.708 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5605 1.48e-01 0.256 0.000 0.560 0.004 0.000 0.180
#> EE97212E-8D5D-4548-8DD2-317049601FDB 5 0.6928 -2.12e-01 0.032 0.372 0.008 0.160 0.412 0.016
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 6 0.4128 -2.87e-01 0.488 0.004 0.000 0.004 0.000 0.504
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 6 0.2860 5.96e-01 0.068 0.028 0.000 0.032 0.000 0.872
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.4528 4.52e-02 0.544 0.008 0.428 0.000 0.000 0.020
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0508 5.62e-01 0.004 0.012 0.000 0.000 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.7218 3.49e-01 0.004 0.116 0.160 0.412 0.308 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 6 0.4689 5.16e-01 0.088 0.004 0.024 0.152 0.000 0.732
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 6 0.6122 3.03e-01 0.304 0.048 0.040 0.044 0.000 0.564
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.4264 1.89e-01 0.000 0.492 0.000 0.016 0.492 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3731 2.60e-01 0.004 0.736 0.000 0.020 0.240 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6088 5.84e-01 0.564 0.028 0.212 0.004 0.000 0.192
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2231 5.97e-01 0.048 0.016 0.000 0.028 0.000 0.908
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4564 1.16e-01 0.008 0.000 0.500 0.472 0.020 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 6 0.1485 6.11e-01 0.028 0.004 0.000 0.024 0.000 0.944
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 6 0.6656 4.76e-01 0.156 0.140 0.000 0.144 0.004 0.556
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 5 0.4317 -1.41e-01 0.008 0.464 0.000 0.008 0.520 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.3036 5.23e-01 0.124 0.008 0.000 0.028 0.000 0.840
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.7905 -4.20e-02 0.140 0.440 0.016 0.112 0.036 0.256
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3054 5.96e-01 0.116 0.000 0.840 0.004 0.000 0.040
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6219 -4.39e-03 0.024 0.008 0.440 0.404 0.124 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.8807 1.35e-02 0.088 0.364 0.048 0.260 0.152 0.088
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 6 0.6874 4.43e-01 0.180 0.156 0.000 0.124 0.008 0.532
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.2636 5.17e-01 0.000 0.120 0.004 0.016 0.860 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5860 5.29e-01 0.552 0.004 0.016 0.140 0.000 0.288
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3448 6.28e-01 0.716 0.000 0.004 0.000 0.000 0.280
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 5 0.6708 -1.87e-01 0.008 0.060 0.132 0.352 0.448 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5939 3.46e-01 0.492 0.052 0.016 0.040 0.000 0.400
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.4291 1.64e-02 0.356 0.008 0.000 0.016 0.000 0.620
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.6981 4.38e-01 0.140 0.200 0.000 0.152 0.004 0.504
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.4411 1.10e-01 0.012 0.628 0.000 0.020 0.340 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4413 1.75e-01 0.008 0.496 0.000 0.012 0.484 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.8857 -7.67e-02 0.224 0.264 0.280 0.040 0.040 0.152
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.0862 5.62e-01 0.004 0.016 0.000 0.008 0.972 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 6 0.4093 -8.15e-02 0.404 0.012 0.000 0.000 0.000 0.584
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 5 0.3121 5.37e-01 0.004 0.180 0.000 0.012 0.804 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.6365 5.05e-01 0.132 0.120 0.004 0.152 0.000 0.592
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 6 0.2201 6.06e-01 0.032 0.028 0.000 0.028 0.000 0.912
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.8067 2.38e-01 0.344 0.100 0.312 0.064 0.000 0.180
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1674 6.04e-01 0.068 0.000 0.924 0.004 0.000 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.3583 3.54e-01 0.004 0.260 0.000 0.008 0.728 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 6 0.7009 4.09e-01 0.144 0.228 0.000 0.152 0.000 0.476
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3855 6.38e-01 0.704 0.000 0.024 0.000 0.000 0.272
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.6725 2.77e-01 0.204 0.112 0.000 0.144 0.004 0.536
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 5 0.5641 2.33e-01 0.004 0.180 0.008 0.216 0.592 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.8099 1.52e-02 0.140 0.468 0.060 0.108 0.024 0.200
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.4461 -1.63e-01 0.004 0.512 0.000 0.020 0.464 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.6139 -2.38e-01 0.008 0.016 0.132 0.412 0.432 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.6701 4.43e-02 0.416 0.056 0.396 0.012 0.000 0.120
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.5398 2.27e-01 0.004 0.040 0.348 0.576 0.020 0.012
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.3860 5.18e-01 0.236 0.000 0.728 0.000 0.000 0.036
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.8382 -9.18e-02 0.108 0.312 0.032 0.292 0.024 0.232
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.3121 5.94e-01 0.116 0.000 0.836 0.004 0.000 0.044
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.3551 5.26e-01 0.048 0.000 0.784 0.168 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 6 0.7859 3.36e-01 0.140 0.264 0.000 0.152 0.040 0.404
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.3345 5.36e-01 0.004 0.112 0.004 0.052 0.828 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 6 0.6982 4.11e-01 0.140 0.228 0.000 0.152 0.000 0.480
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.8561 -9.69e-02 0.116 0.340 0.304 0.048 0.156 0.036
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.3784 6.15e-01 0.048 0.036 0.000 0.108 0.000 0.808
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.4067 2.40e-01 0.008 0.548 0.000 0.000 0.444 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.5765 4.22e-01 0.136 0.148 0.000 0.056 0.008 0.652
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1588 6.05e-01 0.072 0.000 0.924 0.004 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 6 0.4232 5.69e-01 0.096 0.016 0.004 0.112 0.000 0.772
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4387 2.81e-01 0.016 0.584 0.000 0.008 0.392 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 6 0.5019 5.05e-01 0.096 0.012 0.024 0.156 0.000 0.712
#> 4D361EA8-1F79-4B89-841B-87F83215D805 6 0.5209 3.67e-01 0.312 0.048 0.000 0.036 0.000 0.604
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.4841 2.69e-01 0.024 0.532 0.000 0.020 0.424 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.0291 5.61e-01 0.004 0.004 0.000 0.000 0.992 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 6 0.3007 6.18e-01 0.020 0.040 0.000 0.080 0.000 0.860
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.2400 5.07e-01 0.004 0.116 0.000 0.008 0.872 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 5 0.2442 5.44e-01 0.000 0.144 0.000 0.004 0.852 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.0777 5.54e-01 0.004 0.024 0.000 0.000 0.972 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.4960 1.33e-01 0.020 0.000 0.356 0.584 0.000 0.040
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 5 0.0837 5.55e-01 0.004 0.020 0.000 0.004 0.972 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 6 0.5484 5.04e-01 0.104 0.016 0.028 0.184 0.000 0.668
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#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 5 0.6103 -2.49e-01 0.052 0.432 0.000 0.040 0.452 0.024
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.3895 2.53e-01 0.008 0.700 0.000 0.012 0.280 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 6 0.1820 5.92e-01 0.044 0.012 0.000 0.016 0.000 0.928
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 6 0.4551 5.96e-01 0.080 0.044 0.004 0.112 0.000 0.760
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 6 0.6145 5.33e-01 0.100 0.096 0.008 0.180 0.000 0.616
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 6 0.6273 5.06e-01 0.128 0.144 0.000 0.136 0.000 0.592
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.1728 5.96e-01 0.064 0.004 0.924 0.008 0.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 5 0.4165 1.69e-01 0.004 0.308 0.000 0.024 0.664 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.4046 2.83e-01 0.008 0.620 0.000 0.004 0.368 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 5 0.5323 3.15e-01 0.008 0.204 0.000 0.164 0.624 0.000
#> 80936433-AA91-4219-98F1-706C36298060 5 0.6243 -2.90e-01 0.008 0.008 0.180 0.396 0.408 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.5242 2.78e-01 0.016 0.012 0.264 0.640 0.000 0.068
#> 241F589C-D559-43D7-8340-31EBCEB36E14 6 0.7573 3.17e-01 0.124 0.244 0.008 0.252 0.000 0.372
#> D85CB054-7F54-4383-96C0-6C99761B84E7 6 0.1858 5.86e-01 0.052 0.012 0.000 0.012 0.000 0.924
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 6 0.3651 3.66e-01 0.224 0.008 0.000 0.016 0.000 0.752
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 5 0.6163 -2.07e-01 0.012 0.016 0.124 0.400 0.448 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 6 0.4093 1.31e-01 0.324 0.012 0.000 0.008 0.000 0.656
#> 17CA5D73-4384-4645-83F8-587847043DD2 6 0.1820 5.89e-01 0.044 0.012 0.000 0.016 0.000 0.928
#> 40467950-A95C-4731-AD93-0A128442C837 6 0.5812 5.34e-01 0.128 0.108 0.000 0.120 0.000 0.644
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 6 0.7586 3.38e-01 0.148 0.284 0.000 0.152 0.016 0.400
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 6 0.4584 5.93e-01 0.068 0.080 0.000 0.096 0.000 0.756
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#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.4547 3.45e-02 0.552 0.004 0.420 0.004 0.000 0.020
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.6635 2.18e-01 0.008 0.324 0.012 0.408 0.244 0.004
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.7406 -7.99e-02 0.280 0.384 0.000 0.116 0.004 0.216
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 6 0.2519 6.02e-01 0.044 0.016 0.000 0.048 0.000 0.892
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.7229 -1.12e-01 0.100 0.400 0.396 0.064 0.016 0.024
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 6 0.7308 3.69e-01 0.156 0.264 0.000 0.148 0.004 0.428
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 6 0.4159 4.02e-01 0.300 0.020 0.000 0.008 0.000 0.672
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.4662 6.47e-01 0.688 0.000 0.140 0.000 0.000 0.172
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.7487 -2.50e-01 0.136 0.368 0.000 0.148 0.012 0.336
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 6 0.7486 3.26e-01 0.192 0.172 0.004 0.124 0.024 0.484
#> D9364524-CD1F-4C45-A2EF-8CB401487001 6 0.7286 3.88e-01 0.148 0.224 0.004 0.176 0.000 0.448
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.4393 3.67e-01 0.500 0.000 0.004 0.016 0.000 0.480
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.3979 2.29e-01 0.000 0.540 0.000 0.004 0.456 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.7485 2.42e-01 0.048 0.432 0.008 0.224 0.256 0.032
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.4678 5.43e-01 0.080 0.048 0.756 0.108 0.000 0.008
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 5 0.4531 1.76e-01 0.004 0.352 0.000 0.036 0.608 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4097 3.49e-01 0.504 0.000 0.008 0.000 0.000 0.488
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.7521 1.71e-01 0.112 0.548 0.012 0.096 0.092 0.140
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.4474 6.51e-01 0.704 0.000 0.108 0.000 0.000 0.188
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.1701 5.75e-01 0.008 0.000 0.920 0.072 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 6 0.3836 6.07e-01 0.056 0.040 0.000 0.096 0.000 0.808
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.4446 2.46e-01 0.004 0.532 0.000 0.020 0.444 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.6939 4.84e-01 0.004 0.156 0.124 0.548 0.156 0.012
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 6 0.4231 -9.07e-05 0.364 0.012 0.000 0.008 0.000 0.616
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.8335 -3.43e-02 0.128 0.392 0.008 0.140 0.080 0.252
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.3248 5.10e-01 0.004 0.224 0.000 0.004 0.768 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 5 0.4241 1.42e-01 0.004 0.348 0.000 0.020 0.628 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4338 3.08e-01 0.492 0.000 0.000 0.020 0.000 0.488
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2001 6.03e-01 0.092 0.000 0.900 0.004 0.000 0.004
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6362 -6.52e-02 0.444 0.040 0.396 0.112 0.000 0.008
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.4238 6.06e-01 0.060 0.056 0.000 0.104 0.000 0.780
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 5 0.3087 5.37e-01 0.004 0.176 0.000 0.012 0.808 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.2442 5.15e-01 0.004 0.144 0.000 0.000 0.852 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.6304 1.63e-01 0.000 0.320 0.004 0.400 0.272 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.3002 5.95e-01 0.100 0.000 0.848 0.004 0.000 0.048
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 6 0.5371 5.63e-01 0.112 0.092 0.000 0.108 0.000 0.688
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4403 3.45e-01 0.520 0.012 0.000 0.008 0.000 0.460
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1327 6.04e-01 0.064 0.000 0.936 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 6 0.4107 5.97e-01 0.064 0.056 0.000 0.088 0.000 0.792
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.8188 2.34e-01 0.188 0.268 0.400 0.064 0.040 0.040
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.2362 5.53e-01 0.004 0.000 0.860 0.136 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4063 6.44e-01 0.712 0.000 0.028 0.008 0.000 0.252
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 6 0.4219 8.16e-03 0.360 0.012 0.000 0.008 0.000 0.620
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 6 0.1798 6.04e-01 0.028 0.020 0.000 0.020 0.000 0.932
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.4103 2.33e-01 0.004 0.544 0.000 0.004 0.448 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 5 0.6386 3.25e-02 0.004 0.412 0.040 0.128 0.416 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.7857 -2.89e-01 0.164 0.336 0.000 0.144 0.028 0.328
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.5877 4.96e-01 0.184 0.096 0.652 0.044 0.004 0.020
#> B23A1419-0406-48BF-813B-B6ED6FD98789 6 0.2777 6.13e-01 0.048 0.036 0.000 0.036 0.000 0.880
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.4313 4.40e-01 0.004 0.372 0.000 0.020 0.604 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.4400 1.63e-01 0.012 0.524 0.000 0.008 0.456 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.4238 -9.02e-02 0.404 0.008 0.000 0.008 0.000 0.580
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 6 0.2432 5.81e-01 0.072 0.020 0.000 0.016 0.000 0.892
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3307 5.78e-01 0.108 0.000 0.820 0.000 0.000 0.072
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.1952 5.88e-01 0.052 0.012 0.000 0.016 0.000 0.920
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 6 0.4146 4.85e-01 0.212 0.032 0.000 0.020 0.000 0.736
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.4408 1.59e-01 0.008 0.512 0.000 0.012 0.468 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.5605 5.68e-01 0.092 0.096 0.008 0.124 0.000 0.680
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.8682 -5.16e-03 0.080 0.240 0.028 0.312 0.076 0.264
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.3966 -1.41e-01 0.444 0.000 0.000 0.004 0.000 0.552
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.4393 -1.13e-01 0.008 0.448 0.000 0.012 0.532 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.3590 6.11e-01 0.060 0.040 0.000 0.072 0.000 0.828
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.4612 -1.49e-01 0.424 0.012 0.000 0.020 0.000 0.544
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6965 3.05e-01 0.368 0.016 0.252 0.028 0.000 0.336
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4274 3.02e-01 0.008 0.000 0.600 0.380 0.000 0.012
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 6 0.3732 5.80e-01 0.092 0.044 0.000 0.048 0.000 0.816
#> E678189F-D5CF-4C45-8E53-58ECB8448058 6 0.7235 1.15e-01 0.248 0.012 0.144 0.128 0.000 0.468
#> C56C7ED7-A684-40CC-B426-B108E2248467 5 0.5789 2.35e-01 0.004 0.204 0.008 0.216 0.568 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.5237 2.25e-01 0.000 0.276 0.004 0.120 0.600 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7559 3.43e-01 0.096 0.500 0.016 0.060 0.248 0.080
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.8041 3.85e-02 0.072 0.360 0.024 0.328 0.180 0.036
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4090 3.01e-01 0.008 0.000 0.604 0.384 0.000 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5086 3.12e-01 0.184 0.000 0.648 0.004 0.000 0.164
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.1991 5.92e-01 0.044 0.012 0.000 0.024 0.000 0.920
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.4247 4.66e-01 0.296 0.000 0.664 0.000 0.000 0.040
#> 79BA86D9-466F-48D7-B64B-F933B6995716 6 0.6968 4.18e-01 0.164 0.208 0.000 0.140 0.000 0.488
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 5 0.4412 -1.17e-01 0.008 0.480 0.000 0.012 0.500 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.2426 6.04e-01 0.044 0.012 0.000 0.048 0.000 0.896
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.3834 3.54e-01 0.000 0.232 0.000 0.036 0.732 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3362 5.76e-01 0.096 0.000 0.824 0.004 0.000 0.076
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 6 0.1382 5.94e-01 0.036 0.008 0.000 0.008 0.000 0.948
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 6 0.6598 4.63e-01 0.084 0.060 0.040 0.260 0.000 0.556
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.6028 3.03e-01 0.304 0.036 0.544 0.004 0.000 0.112
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 5 0.4009 4.52e-01 0.000 0.288 0.000 0.028 0.684 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 6 0.2893 6.16e-01 0.024 0.032 0.000 0.076 0.000 0.868
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5711 5.91e-01 0.612 0.000 0.040 0.124 0.000 0.224
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.6646 3.76e-01 0.112 0.020 0.104 0.188 0.000 0.576
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.1003 6.01e-01 0.028 0.004 0.000 0.004 0.000 0.964
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 5 0.6034 1.64e-01 0.000 0.328 0.000 0.260 0.412 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 6 0.3944 -1.43e-01 0.428 0.000 0.000 0.004 0.000 0.568
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 5 0.6221 -1.15e-01 0.008 0.108 0.032 0.400 0.452 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3078 5.15e-01 0.012 0.000 0.796 0.192 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.3493 5.08e-01 0.008 0.228 0.000 0.008 0.756 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 6 0.3411 5.02e-01 0.160 0.024 0.000 0.012 0.000 0.804
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.5105 5.72e-01 0.084 0.092 0.000 0.112 0.000 0.712
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5980 6.26e-01 0.604 0.004 0.160 0.044 0.000 0.188
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.3461 6.13e-01 0.048 0.040 0.000 0.076 0.000 0.836
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.781 0.896 0.950 0.4925 0.508 0.508
#> 3 3 0.803 0.820 0.928 0.3207 0.767 0.574
#> 4 4 0.637 0.715 0.827 0.1302 0.821 0.551
#> 5 5 0.622 0.580 0.755 0.0666 0.895 0.640
#> 6 6 0.656 0.504 0.735 0.0398 0.850 0.469
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9669 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.0000 0.9669 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.0000 0.9321 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.9669 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9669 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.9321 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.0000 0.9321 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1633 0.9297 0.976 0.024
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.7299 0.7854 0.796 0.204
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.9321 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.9669 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4431 0.8901 0.908 0.092
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9669 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9669 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.9321 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.6973 0.8033 0.812 0.188
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0000 0.9669 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.1184 0.9523 0.016 0.984
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.9669 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9669 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.9996 0.0181 0.512 0.488
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9669 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.1633 0.9297 0.976 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9669 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.7376 0.7801 0.792 0.208
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9669 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.9321 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.9669 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.9321 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1843 0.9282 0.972 0.028
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0000 0.9321 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9669 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.9669 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1633 0.9297 0.976 0.024
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.5294 0.8676 0.880 0.120
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.0000 0.9669 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9669 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.9321 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1633 0.9297 0.976 0.024
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.0672 0.9296 0.992 0.008
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.7139 0.7942 0.804 0.196
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.9896 0.3223 0.560 0.440
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9669 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9321 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0000 0.9669 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.9321 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.8608 0.6128 0.284 0.716
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.9754 0.2299 0.408 0.592
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.7883 0.7436 0.764 0.236
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9669 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9321 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.9321 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.9669 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.9321 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9321 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 2 0.0000 0.9669 0.000 1.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9669 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.9669 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.7219 0.7896 0.800 0.200
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.9669 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.9321 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.9669 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.6887 0.8073 0.816 0.184
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.3879 0.9013 0.924 0.076
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0000 0.9321 1.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0000 0.9321 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.9669 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 2 0.0000 0.9669 0.000 1.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.9321 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1414 0.9303 0.980 0.020
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.9669 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.0000 0.9669 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.9669 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.9669 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.0000 0.9321 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.5059 0.8491 0.888 0.112
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0000 0.9321 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0376 0.9634 0.004 0.996
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.0000 0.9321 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.2423 0.9122 0.960 0.040
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.2423 0.9289 0.040 0.960
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.9669 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.9833 0.1736 0.424 0.576
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.0000 0.9669 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 2 0.5408 0.8330 0.124 0.876
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.9669 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0376 0.9319 0.996 0.004
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.0000 0.9321 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.1633 0.9297 0.976 0.024
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.9669 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.1633 0.9297 0.976 0.024
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.4431 0.8898 0.908 0.092
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.0000 0.9669 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.9669 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.7219 0.7896 0.800 0.200
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0000 0.9669 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.9669 0.000 1.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.9669 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.0000 0.9321 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.9669 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.1633 0.9297 0.976 0.024
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.3584 0.9065 0.932 0.068
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0000 0.9669 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.9669 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0000 0.9321 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.0000 0.9321 1.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.0000 0.9321 1.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0000 0.9321 1.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.9669 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.7139 0.7943 0.804 0.196
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.0000 0.9669 0.000 1.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0000 0.9669 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.9669 0.000 1.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.0000 0.9321 1.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.0000 0.9669 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.9669 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.1633 0.9297 0.976 0.024
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.9669 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.0000 0.9321 1.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 2 0.9833 0.1958 0.424 0.576
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.1633 0.9297 0.976 0.024
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1633 0.9297 0.976 0.024
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0000 0.9669 0.000 1.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.0000 0.9321 1.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0000 0.9669 0.000 1.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.0000 0.9321 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.0000 0.9669 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 2 0.0000 0.9669 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.1633 0.9297 0.976 0.024
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 1 0.0376 0.9309 0.996 0.004
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.1633 0.9297 0.976 0.024
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.9669 0.000 1.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.7139 0.7941 0.804 0.196
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.0000 0.9321 1.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1414 0.9303 0.980 0.020
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 1 0.0000 0.9321 1.000 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.9491 0.4084 0.632 0.368
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.9669 0.000 1.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.6801 0.8115 0.820 0.180
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.9669 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 1 0.0000 0.9321 1.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 1 0.0000 0.9321 1.000 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.2043 0.9390 0.032 0.968
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.9669 0.000 1.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.7219 0.7896 0.800 0.200
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.9669 0.000 1.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.9669 0.000 1.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.1633 0.9297 0.976 0.024
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 1 0.0000 0.9321 1.000 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.1633 0.9297 0.976 0.024
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.9669 0.000 1.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 1 0.0000 0.9321 1.000 0.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 1 0.8909 0.6296 0.692 0.308
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.1633 0.9297 0.976 0.024
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 2 0.9977 -0.0153 0.472 0.528
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.8081 0.7276 0.752 0.248
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.1633 0.9297 0.976 0.024
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 1 0.1633 0.9297 0.976 0.024
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F 2 0.5737 0.8308 0.136 0.864
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0 2 0.0000 0.9669 0.000 1.000
#> D149276E-A961-49D6-8BDA-004E8264A0A1 1 0.1633 0.9297 0.976 0.024
#> D17803A2-4BF2-4382-A544-76E28695214F 1 0.1633 0.9297 0.976 0.024
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6 1 0.0000 0.9321 1.000 0.000
#> 16F5BF94-5103-4973-9432-34FDCC82B6A2 1 0.1633 0.9297 0.976 0.024
#> 293FB23D-72CB-4211-B4ED-9C57412CE9F0 1 0.1633 0.9297 0.976 0.024
#> C99F0CD0-B9EB-45F3-885F-6D0519BF1BF7 2 0.0000 0.9669 0.000 1.000
#> 5B8D1101-572C-4445-81C4-83A6D6115451 1 0.1184 0.9308 0.984 0.016
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#> 985FEEC2-9737-4018-80DF-21A07AB47900 1 0.0000 0.9321 1.000 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.0000 0.9321 1.000 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.9000 0.6148 0.684 0.316
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9669 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.7528 0.7224 0.216 0.784
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.8763 0.6506 0.704 0.296
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.0000 0.9669 0.000 1.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.9833 0.1740 0.424 0.576
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.2948 0.9160 0.948 0.052
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.9669 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.1633 0.9297 0.976 0.024
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 1 0.0000 0.9321 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0000 0.9321 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.9669 0.000 1.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.7219 0.7896 0.800 0.200
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.2423 0.9227 0.960 0.040
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 1 0.0000 0.9321 1.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.1633 0.9447 0.024 0.976
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0000 0.9669 0.000 1.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.9669 0.000 1.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.2236 0.9245 0.964 0.036
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.0000 0.9669 0.000 1.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.9669 0.000 1.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0000 0.9669 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.0000 0.9669 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.9669 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.1633 0.9297 0.976 0.024
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.1633 0.9297 0.976 0.024
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.7376 0.7802 0.792 0.208
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 2 0.7602 0.6857 0.220 0.780
#> B57C849C-28B1-4315-885C-330B9C9482B3 1 0.0000 0.9321 1.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.9669 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.9669 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9669 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.2236 0.9353 0.036 0.964
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.9321 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0000 0.9669 0.000 1.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0376 0.9319 0.996 0.004
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9321 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9669 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9321 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.1633 0.9297 0.976 0.024
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.6973 0.8029 0.812 0.188
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.7056 0.7371 0.192 0.808
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.7376 0.7801 0.792 0.208
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.0000 0.9321 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.0000 0.9321 1.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.0000 0.9669 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.9491 0.4402 0.632 0.368
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.1633 0.9297 0.976 0.024
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.7219 0.7444 0.200 0.800
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.9922 0.2995 0.552 0.448
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.1633 0.9297 0.976 0.024
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0000 0.9321 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.0000 0.9669 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.6148 0.8392 0.848 0.152
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0000 0.9669 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9321 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0000 0.9669 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.0000 0.9669 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.9393 0.4653 0.356 0.644
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9669 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.9321 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.9669 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.0000 0.9321 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.0000 0.9321 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.1633 0.9297 0.976 0.024
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9669 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.0000 0.9669 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9321 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.6247 0.7875 0.156 0.844
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9669 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9669 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9321 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.9321 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.9321 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.7219 0.7896 0.800 0.200
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9669 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9669 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.0000 0.9669 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0000 0.9321 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.6531 0.8236 0.832 0.168
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.9321 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.0000 0.9321 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.6048 0.8429 0.852 0.148
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.7376 0.7804 0.792 0.208
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 1 0.0000 0.9321 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0000 0.9321 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9321 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.1843 0.9281 0.972 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.9669 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0000 0.9669 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.7745 0.7544 0.772 0.228
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.5842 0.8189 0.860 0.140
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.2423 0.9226 0.960 0.040
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9669 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9669 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9321 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1633 0.9297 0.976 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.9321 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.1414 0.9303 0.980 0.020
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1633 0.9297 0.976 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0000 0.9669 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3879 0.9012 0.924 0.076
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.9170 0.5842 0.668 0.332
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9321 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.9669 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.7219 0.7896 0.800 0.200
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9321 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.1633 0.9297 0.976 0.024
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.9321 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.1843 0.9281 0.972 0.028
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0938 0.9312 0.988 0.012
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.9669 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.9669 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9669 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.6801 0.7518 0.180 0.820
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0000 0.9321 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.9321 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1633 0.9297 0.976 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0000 0.9321 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.8443 0.6904 0.728 0.272
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9669 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2043 0.9264 0.968 0.032
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9669 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.9321 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9321 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4161 0.8957 0.916 0.084
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0000 0.9321 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9669 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.2236 0.9246 0.964 0.036
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.9321 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1633 0.9297 0.976 0.024
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1184 0.9308 0.984 0.016
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0000 0.9669 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9321 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9669 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.0000 0.9321 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9669 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1633 0.9297 0.976 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.9460 0.5168 0.636 0.364
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.9321 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5294 0.8676 0.880 0.120
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9480 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.0000 0.9480 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8657 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.9480 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9480 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1289 0.8452 0.032 0.000 0.968
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.5058 0.6087 0.244 0.000 0.756
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9154 1.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.4702 0.6863 0.788 0.000 0.212
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.8657 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.9480 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.9154 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9480 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.2066 0.8904 0.060 0.940 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6140 0.2876 0.596 0.000 0.404
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.9154 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0000 0.9480 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9480 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.9480 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9480 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.8657 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9480 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9154 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9480 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9154 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.4654 0.7113 0.000 0.792 0.208
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.8657 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.1163 0.9250 0.028 0.972 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4452 0.7136 0.808 0.000 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9154 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6154 0.3084 0.592 0.000 0.408
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9480 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.2066 0.8959 0.000 0.940 0.060
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0424 0.9117 0.992 0.000 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.6026 0.3862 0.624 0.000 0.376
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.0424 0.9433 0.008 0.992 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0237 0.9462 0.004 0.996 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.6274 0.1524 0.456 0.000 0.544
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0237 0.9137 0.996 0.000 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.0000 0.8657 0.000 0.000 1.000
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#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.1643 0.9077 0.044 0.956 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9154 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9154 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9480 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9154 1.000 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9154 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9154 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.9154 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9154 1.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.8657 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.6126 0.3012 0.400 0.000 0.600
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.0000 0.9480 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.9154 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0237 0.9137 0.996 0.000 0.004
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.6483 0.1457 0.004 0.544 0.452
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.9154 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0424 0.9117 0.992 0.000 0.008
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.3941 0.7403 0.156 0.000 0.844
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.1411 0.8851 0.964 0.036 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0237 0.9137 0.996 0.000 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.6267 0.1585 0.452 0.548 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0237 0.9137 0.996 0.000 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0237 0.9462 0.004 0.996 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.0000 0.9480 0.000 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.8657 0.000 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9480 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.2448 0.8519 0.924 0.000 0.076
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0237 0.9462 0.004 0.996 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.6140 0.3191 0.596 0.000 0.404
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.8657 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0237 0.9137 0.996 0.000 0.004
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9480 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.0000 0.9480 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9154 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4887 0.6510 0.772 0.228 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.3412 0.8247 0.000 0.876 0.124
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9480 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0237 0.9137 0.996 0.000 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.8657 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6026 0.3860 0.624 0.000 0.376
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9154 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9480 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9480 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.0000 0.9480 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8657 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9154 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.1964 0.8780 0.944 0.000 0.056
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8657 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.9154 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.9156 0.4419 0.256 0.204 0.540
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.8657 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0424 0.9117 0.992 0.000 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9154 1.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.9154 1.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0237 0.9462 0.004 0.996 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0000 0.9480 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.0000 0.9154 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0237 0.8633 0.004 0.000 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9154 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9480 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9480 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9154 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.9154 1.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.8657 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9154 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.9154 1.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0237 0.9462 0.004 0.996 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.9154 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0237 0.9132 0.996 0.004 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0237 0.9137 0.996 0.000 0.004
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0000 0.9480 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9154 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0237 0.9137 0.996 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.6140 0.3188 0.596 0.000 0.404
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0000 0.8657 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9154 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.6140 0.3188 0.596 0.000 0.404
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.9480 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.9480 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0237 0.9462 0.004 0.996 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.5733 0.5198 0.324 0.676 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0000 0.8657 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.6062 0.3435 0.384 0.000 0.616
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0237 0.9137 0.996 0.000 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.8657 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.9154 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9480 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9154 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9480 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.8657 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9154 1.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.9154 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.2165 0.8242 0.064 0.000 0.936
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9480 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9154 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5529 0.5586 0.704 0.000 0.296
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0592 0.9090 0.988 0.000 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9154 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0000 0.9480 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9154 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4605 0.7174 0.000 0.796 0.204
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8657 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9480 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9154 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9154 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0592 0.9090 0.988 0.000 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9154 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.4564 0.6512 0.000 0.328 0.000 0.672
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.2329 0.7805 0.012 0.916 0.072 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2704 0.8292 0.000 0.000 0.876 0.124
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0817 0.8040 0.000 0.976 0.024 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2011 0.7984 0.000 0.920 0.000 0.080
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2892 0.8306 0.068 0.000 0.896 0.036
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.3401 0.7287 0.008 0.000 0.840 0.152
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0817 0.8664 0.976 0.000 0.000 0.024
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6220 0.6314 0.648 0.000 0.104 0.248
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1118 0.8618 0.000 0.000 0.964 0.036
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3528 0.7832 0.000 0.808 0.000 0.192
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3266 0.7694 0.832 0.000 0.000 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2760 0.7994 0.000 0.872 0.000 0.128
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.4855 0.6805 0.004 0.644 0.000 0.352
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.7137 0.3408 0.536 0.304 0.160 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 4 0.4072 0.6134 0.252 0.000 0.000 0.748
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.1247 0.8026 0.012 0.968 0.016 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.2469 0.7961 0.000 0.892 0.000 0.108
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0469 0.8067 0.000 0.988 0.000 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2469 0.7861 0.000 0.892 0.000 0.108
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2469 0.7861 0.000 0.892 0.000 0.108
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2408 0.7833 0.000 0.896 0.000 0.104
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0336 0.8668 0.992 0.008 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.4797 0.7168 0.000 0.720 0.020 0.260
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.1902 0.7841 0.064 0.932 0.000 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.7663 -0.0471 0.408 0.000 0.380 0.212
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0921 0.8659 0.972 0.000 0.000 0.028
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6520 0.6216 0.648 0.008 0.112 0.232
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.3569 0.7850 0.000 0.804 0.000 0.196
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.3157 0.7363 0.000 0.852 0.144 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4158 0.7439 0.768 0.008 0.000 0.224
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.6317 0.6212 0.644 0.000 0.116 0.240
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.4820 0.7213 0.012 0.296 0.000 0.692
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 4 0.3942 0.7653 0.000 0.236 0.000 0.764
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4985 0.1370 0.532 0.000 0.468 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0188 0.8677 0.996 0.004 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.3486 0.7044 0.000 0.188 0.812 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0592 0.8677 0.984 0.000 0.000 0.016
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4941 0.1086 0.564 0.000 0.000 0.436
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 4 0.3975 0.7616 0.000 0.240 0.000 0.760
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.4737 0.7454 0.020 0.252 0.000 0.728
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.4888 0.2657 0.412 0.588 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.3873 0.6399 0.228 0.000 0.000 0.772
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2469 0.7861 0.000 0.892 0.000 0.108
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.1722 0.8544 0.944 0.008 0.000 0.048
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.3958 0.7564 0.160 0.000 0.816 0.024
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.1677 0.8012 0.000 0.948 0.040 0.012
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 4 0.5038 0.4721 0.336 0.000 0.012 0.652
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.5151 0.2435 0.464 0.004 0.000 0.532
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 4 0.3975 0.7616 0.000 0.240 0.000 0.760
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 4 0.4040 0.7603 0.000 0.248 0.000 0.752
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.9856 0.0379 0.332 0.196 0.248 0.224
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0336 0.8073 0.000 0.992 0.000 0.008
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0921 0.8656 0.972 0.000 0.000 0.028
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0336 0.8073 0.000 0.992 0.000 0.008
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#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.1557 0.8049 0.000 0.944 0.000 0.056
#> 80936433-AA91-4219-98F1-706C36298060 2 0.4252 0.6514 0.000 0.744 0.252 0.004
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 3 0.5143 0.4177 0.012 0.360 0.628 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 4 0.4422 0.4665 0.008 0.256 0.000 0.736
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0188 0.8684 0.996 0.000 0.000 0.004
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.1174 0.8059 0.000 0.968 0.020 0.012
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0817 0.8664 0.976 0.000 0.000 0.024
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 4 0.4998 0.1616 0.488 0.000 0.000 0.512
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 4 0.4996 0.1991 0.484 0.000 0.000 0.516
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.1474 0.8549 0.948 0.000 0.000 0.052
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.1792 0.8533 0.000 0.000 0.932 0.068
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.7342 0.0444 0.432 0.000 0.412 0.156
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.2402 0.7784 0.012 0.912 0.076 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.2530 0.7895 0.888 0.000 0.000 0.112
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 4 0.5018 0.7313 0.000 0.144 0.088 0.768
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.4250 0.5456 0.724 0.000 0.000 0.276
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.2345 0.8334 0.900 0.000 0.000 0.100
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.4663 0.7554 0.148 0.000 0.788 0.064
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.4647 0.6130 0.288 0.008 0.000 0.704
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1022 0.8639 0.968 0.000 0.000 0.032
#> D9364524-CD1F-4C45-A2EF-8CB401487001 4 0.5416 0.6759 0.112 0.148 0.000 0.740
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 4 0.3942 0.7642 0.000 0.236 0.000 0.764
#> 72DDC907-0901-4E61-83CF-38500D03FABC 2 0.1978 0.7792 0.068 0.928 0.000 0.004
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.1474 0.8058 0.000 0.948 0.000 0.052
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4401 0.5751 0.724 0.000 0.272 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 4 0.3907 0.7659 0.000 0.232 0.000 0.768
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.6621 0.5253 0.616 0.000 0.244 0.140
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3658 0.8139 0.020 0.000 0.836 0.144
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0336 0.8676 0.992 0.008 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 4 0.3942 0.7642 0.000 0.236 0.000 0.764
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.2861 0.7645 0.016 0.888 0.096 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0188 0.8684 0.996 0.000 0.000 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.5558 0.3401 0.608 0.028 0.000 0.364
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.4933 0.7067 0.000 0.688 0.016 0.296
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.2408 0.7883 0.000 0.896 0.000 0.104
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.4292 0.7664 0.796 0.008 0.016 0.180
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0469 0.8663 0.988 0.012 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 4 0.4072 0.7512 0.000 0.252 0.000 0.748
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.4989 -0.1377 0.000 0.528 0.000 0.472
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.2402 0.7784 0.012 0.912 0.076 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.6703 0.5793 0.612 0.000 0.156 0.232
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1022 0.8650 0.968 0.000 0.000 0.032
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.9458 0.1649 0.136 0.408 0.224 0.232
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1520 0.8611 0.956 0.000 0.020 0.024
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0707 0.8673 0.980 0.000 0.000 0.020
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0592 0.8677 0.984 0.000 0.000 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 4 0.3942 0.7642 0.000 0.236 0.000 0.764
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0592 0.8073 0.000 0.984 0.000 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 4 0.4406 0.5627 0.300 0.000 0.000 0.700
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 4 0.4389 0.6973 0.000 0.072 0.116 0.812
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0336 0.8678 0.992 0.000 0.000 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4331 0.7310 0.000 0.712 0.000 0.288
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 4 0.3975 0.7616 0.000 0.240 0.000 0.760
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1474 0.8581 0.948 0.000 0.000 0.052
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0592 0.8677 0.984 0.000 0.000 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.4999 0.3893 0.000 0.492 0.000 0.508
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1792 0.8394 0.932 0.068 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.3311 0.7597 0.828 0.172 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.2011 0.7938 0.000 0.920 0.000 0.080
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0188 0.8677 0.996 0.004 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.7097 0.5225 0.584 0.004 0.180 0.232
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0469 0.8622 0.000 0.012 0.988 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0921 0.8659 0.972 0.000 0.000 0.028
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.5274 0.7060 0.724 0.008 0.036 0.232
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0336 0.8063 0.000 0.992 0.000 0.008
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.2011 0.8009 0.000 0.920 0.000 0.080
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 4 0.4720 0.7528 0.000 0.188 0.044 0.768
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.3649 0.6293 0.204 0.796 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0817 0.8569 0.000 0.024 0.976 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.4356 0.5575 0.292 0.000 0.708 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0469 0.8678 0.988 0.000 0.000 0.012
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2921 0.8223 0.000 0.000 0.860 0.140
#> 79BA86D9-466F-48D7-B64B-F933B6995716 4 0.4679 0.4960 0.352 0.000 0.000 0.648
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3569 0.6246 0.000 0.804 0.000 0.196
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.8684 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2281 0.7924 0.000 0.904 0.000 0.096
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0592 0.8677 0.984 0.000 0.000 0.016
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4262 0.7372 0.756 0.008 0.000 0.236
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4104 0.7994 0.080 0.000 0.832 0.088
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0592 0.8067 0.000 0.984 0.000 0.016
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0469 0.8678 0.988 0.000 0.000 0.012
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.6371 0.6089 0.664 0.004 0.200 0.132
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3852 0.7678 0.800 0.008 0.000 0.192
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0188 0.8684 0.996 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0376 0.8064 0.004 0.992 0.004 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0188 0.8682 0.996 0.000 0.000 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2469 0.7799 0.000 0.892 0.000 0.108
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8670 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.3400 0.7132 0.000 0.820 0.000 0.180
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0707 0.8673 0.980 0.000 0.000 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.2149 0.8296 0.912 0.000 0.000 0.088
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0657 0.8681 0.984 0.004 0.000 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0592 0.8674 0.984 0.000 0.000 0.016
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5235 0.42988 0.000 0.620 0.000 0.312 0.068
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.3996 0.53957 0.228 0.000 0.012 0.752 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0404 0.81719 0.000 0.012 0.988 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0324 0.70654 0.004 0.000 0.004 0.992 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.3639 0.69583 0.000 0.024 0.000 0.792 0.184
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.5098 0.58366 0.004 0.208 0.696 0.000 0.092
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.1965 0.77021 0.000 0.096 0.904 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4985 0.65453 0.680 0.076 0.000 0.000 0.244
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 5 0.5334 0.40795 0.244 0.104 0.000 0.000 0.652
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1341 0.79850 0.000 0.000 0.944 0.000 0.056
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.4718 0.50674 0.000 0.016 0.000 0.540 0.444
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.6688 0.28536 0.404 0.356 0.000 0.000 0.240
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 4 0.4371 0.61942 0.000 0.012 0.000 0.644 0.344
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.3630 0.29267 0.000 0.016 0.000 0.204 0.780
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.4557 0.15589 0.584 0.000 0.000 0.404 0.012
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.4558 0.54739 0.060 0.724 0.000 0.000 0.216
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.2463 0.65593 0.100 0.000 0.004 0.888 0.008
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 4 0.3999 0.62250 0.000 0.000 0.000 0.656 0.344
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.0451 0.71105 0.000 0.004 0.000 0.988 0.008
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 4 0.5215 0.59960 0.000 0.056 0.000 0.592 0.352
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 4 0.5404 0.66154 0.000 0.152 0.000 0.664 0.184
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.1410 0.72065 0.940 0.000 0.000 0.000 0.060
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 4 0.3835 0.59890 0.000 0.244 0.000 0.744 0.012
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0451 0.70995 0.988 0.000 0.000 0.004 0.008
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.4088 0.08411 0.000 0.008 0.000 0.304 0.688
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 4 0.1043 0.69423 0.040 0.000 0.000 0.960 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.8338 -0.23415 0.292 0.348 0.160 0.000 0.200
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.6009 0.54996 0.580 0.180 0.000 0.000 0.240
#> 97C34F1F-2002-4771-8D99-511EA08591CD 5 0.4016 0.47222 0.272 0.000 0.012 0.000 0.716
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 4 0.4726 0.56255 0.000 0.020 0.000 0.580 0.400
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.1788 0.68100 0.004 0.000 0.056 0.932 0.008
#> C06D8112-0FA0-4607-988D-589D8694743F 5 0.3561 0.47425 0.260 0.000 0.000 0.000 0.740
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.5472 0.37330 0.260 0.108 0.000 0.000 0.632
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.5284 0.33932 0.036 0.332 0.000 0.616 0.016
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.2966 0.74920 0.000 0.848 0.000 0.136 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4307 0.07692 0.504 0.000 0.496 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0324 0.70821 0.992 0.000 0.000 0.004 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.2377 0.74901 0.000 0.000 0.872 0.128 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4730 0.66444 0.688 0.052 0.000 0.000 0.260
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.5039 -0.06614 0.456 0.512 0.000 0.000 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.3496 0.68479 0.000 0.788 0.000 0.200 0.012
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.3548 0.70600 0.004 0.796 0.000 0.188 0.012
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0162 0.81967 0.000 0.004 0.996 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0290 0.81832 0.000 0.000 0.992 0.008 0.000
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#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.4527 0.66500 0.700 0.040 0.000 0.000 0.260
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 5 0.2690 0.57786 0.156 0.000 0.000 0.000 0.844
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.5690 0.13745 0.004 0.068 0.492 0.000 0.436
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 5 0.5403 0.12882 0.004 0.052 0.388 0.000 0.556
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.3988 0.70296 0.768 0.000 0.000 0.036 0.196
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 5 0.4696 -0.29927 0.000 0.016 0.000 0.428 0.556
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 5 0.4704 0.30016 0.000 0.000 0.112 0.152 0.736
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.3452 0.57450 0.756 0.244 0.000 0.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 4 0.5738 0.63174 0.000 0.132 0.000 0.604 0.264
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.2339 0.74287 0.004 0.892 0.004 0.000 0.100
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0162 0.71014 0.996 0.000 0.000 0.000 0.004
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 4 0.4735 0.48306 0.000 0.016 0.000 0.524 0.460
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.3398 0.69829 0.780 0.004 0.000 0.000 0.216
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.2909 0.71973 0.848 0.012 0.000 0.000 0.140
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 4 0.5192 0.64868 0.000 0.076 0.000 0.644 0.280
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 5 0.3109 0.54589 0.200 0.000 0.000 0.000 0.800
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.6601 0.36953 0.460 0.292 0.000 0.000 0.248
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.3730 0.57108 0.000 0.000 0.712 0.000 0.288
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.0963 0.69613 0.000 0.000 0.036 0.964 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 4 0.4655 0.45618 0.000 0.012 0.000 0.512 0.476
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.2690 0.73371 0.000 0.844 0.000 0.156 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 5 0.4369 0.51589 0.208 0.052 0.000 0.000 0.740
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.1608 0.78556 0.000 0.928 0.000 0.072 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 4 0.3305 0.68619 0.000 0.000 0.000 0.776 0.224
#> E789661A-C027-405D-9F76-E6D52CE3018B 4 0.3752 0.46548 0.000 0.292 0.000 0.708 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.2773 0.72614 0.000 0.836 0.000 0.164 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.1478 0.78887 0.000 0.936 0.000 0.064 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0566 0.70363 0.984 0.000 0.000 0.012 0.004
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.2824 0.71986 0.864 0.020 0.000 0.000 0.116
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 2 0.4622 0.15514 0.440 0.548 0.000 0.000 0.012
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.3003 0.69808 0.000 0.188 0.812 0.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 4 0.2843 0.63886 0.000 0.144 0.000 0.848 0.008
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.1410 0.78850 0.000 0.940 0.000 0.060 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 4 0.3835 0.67250 0.000 0.008 0.000 0.732 0.260
#> 80936433-AA91-4219-98F1-706C36298060 4 0.4161 0.34980 0.000 0.000 0.392 0.608 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 3 0.5591 0.41201 0.064 0.000 0.576 0.352 0.008
#> 241F589C-D559-43D7-8340-31EBCEB36E14 5 0.4062 0.42269 0.000 0.196 0.000 0.040 0.764
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4461 0.68472 0.728 0.052 0.000 0.000 0.220
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0963 0.71939 0.964 0.000 0.000 0.000 0.036
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 4 0.1121 0.69758 0.000 0.000 0.044 0.956 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.4873 0.65993 0.688 0.068 0.000 0.000 0.244
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 2 0.5263 0.43319 0.240 0.660 0.000 0.000 0.100
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.4627 0.20532 0.544 0.444 0.000 0.000 0.012
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.5115 0.66516 0.676 0.092 0.000 0.000 0.232
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.2424 0.74581 0.000 0.000 0.868 0.000 0.132
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 5 0.5883 0.40610 0.268 0.012 0.108 0.000 0.612
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.2429 0.66398 0.068 0.000 0.020 0.904 0.008
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.3056 0.68059 0.860 0.112 0.000 0.008 0.020
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0324 0.70821 0.992 0.000 0.000 0.004 0.004
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.1197 0.78101 0.000 0.952 0.048 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.3177 0.59555 0.792 0.208 0.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 5 0.5548 -0.10516 0.440 0.068 0.000 0.000 0.492
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.7018 0.30308 0.048 0.180 0.536 0.000 0.236
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.3011 0.73036 0.140 0.844 0.000 0.016 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.4657 0.59614 0.668 0.036 0.000 0.000 0.296
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.5347 0.35522 0.024 0.556 0.000 0.020 0.400
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0162 0.71014 0.996 0.000 0.000 0.000 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.2179 0.76674 0.000 0.888 0.000 0.112 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.3612 0.53956 0.228 0.000 0.000 0.764 0.008
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.1851 0.78039 0.000 0.088 0.912 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 4 0.0703 0.71192 0.000 0.024 0.000 0.976 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.4503 0.52434 0.700 0.028 0.268 0.000 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0510 0.79011 0.000 0.984 0.000 0.016 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 5 0.6146 -0.04352 0.392 0.116 0.004 0.000 0.488
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.4894 0.20006 0.024 0.000 0.520 0.000 0.456
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0324 0.70821 0.992 0.000 0.000 0.004 0.004
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1908 0.77774 0.000 0.908 0.000 0.092 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.3678 0.59125 0.168 0.000 0.020 0.804 0.008
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4337 0.69311 0.744 0.052 0.000 0.000 0.204
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.6920 -0.07795 0.324 0.476 0.000 0.024 0.176
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.3934 0.21441 0.000 0.016 0.000 0.244 0.740
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 4 0.4852 0.68437 0.000 0.100 0.000 0.716 0.184
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.4297 0.02989 0.528 0.000 0.000 0.000 0.472
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0693 0.70170 0.980 0.000 0.000 0.012 0.008
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.3336 0.64860 0.000 0.772 0.000 0.228 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.5369 0.53523 0.000 0.660 0.000 0.216 0.124
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.2395 0.66644 0.072 0.000 0.016 0.904 0.008
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0162 0.71014 0.996 0.000 0.000 0.000 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7 5 0.5586 0.29236 0.308 0.068 0.012 0.000 0.612
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.6278 0.49114 0.536 0.212 0.000 0.000 0.252
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.3231 0.46437 0.004 0.000 0.000 0.196 0.800
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4732 0.67886 0.716 0.076 0.000 0.000 0.208
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4765 0.67206 0.704 0.068 0.000 0.000 0.228
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.4879 0.66744 0.696 0.076 0.000 0.000 0.228
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2329 0.75922 0.000 0.876 0.000 0.124 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 4 0.0290 0.70873 0.000 0.008 0.000 0.992 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.3085 0.71031 0.032 0.852 0.000 0.000 0.116
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.1493 0.77821 0.000 0.948 0.028 0.000 0.024
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4495 0.69122 0.736 0.064 0.000 0.000 0.200
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.4497 -0.08603 0.000 0.016 0.000 0.352 0.632
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.2329 0.75943 0.000 0.876 0.000 0.124 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.6323 0.45073 0.516 0.192 0.000 0.000 0.292
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0162 0.81967 0.000 0.004 0.996 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.5110 0.65627 0.680 0.096 0.000 0.000 0.224
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.4118 0.39087 0.000 0.336 0.000 0.660 0.004
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3957 0.38166 0.712 0.000 0.000 0.280 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.4436 0.17568 0.596 0.000 0.000 0.396 0.008
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.71175 1.000 0.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.4016 0.70385 0.000 0.092 0.000 0.796 0.112
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0579 0.70402 0.984 0.000 0.000 0.008 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0404 0.71515 0.988 0.000 0.000 0.000 0.012
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 5 0.3579 0.50263 0.240 0.004 0.000 0.000 0.756
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.5909 0.56617 0.592 0.164 0.000 0.000 0.244
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.3177 0.53899 0.208 0.000 0.000 0.000 0.792
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.0162 0.70917 0.000 0.004 0.000 0.996 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 4 0.3109 0.68479 0.000 0.000 0.000 0.800 0.200
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.78690 0.000 1.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.2648 0.59509 0.152 0.000 0.000 0.848 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.2424 0.72871 0.132 0.000 0.868 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.3491 0.69343 0.768 0.004 0.000 0.000 0.228
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.5073 0.55312 0.000 0.100 0.688 0.000 0.212
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.3177 0.61280 0.208 0.792 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 4 0.2798 0.66919 0.000 0.140 0.000 0.852 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0324 0.70821 0.992 0.000 0.000 0.004 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.4588 0.68251 0.000 0.060 0.000 0.720 0.220
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4904 0.66060 0.688 0.072 0.000 0.000 0.240
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.2891 0.56337 0.176 0.000 0.000 0.000 0.824
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.6909 0.14028 0.008 0.360 0.400 0.000 0.232
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 4 0.0579 0.71173 0.000 0.008 0.000 0.984 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3461 0.69526 0.772 0.004 0.000 0.000 0.224
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.6548 0.04980 0.420 0.000 0.200 0.000 0.380
#> EB7883EB-0079-4548-9132-169E94A698BA 5 0.4101 0.40976 0.372 0.000 0.000 0.000 0.628
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4369 0.69120 0.740 0.052 0.000 0.000 0.208
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0898 0.70015 0.020 0.000 0.000 0.972 0.008
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4305 0.69499 0.748 0.052 0.000 0.000 0.200
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.1671 0.67215 0.000 0.000 0.000 0.924 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.82054 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 4 0.5946 0.60009 0.000 0.224 0.000 0.592 0.184
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5004 0.66799 0.692 0.092 0.000 0.000 0.216
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5526 0.61310 0.648 0.200 0.000 0.000 0.152
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.1478 0.71464 0.936 0.000 0.000 0.000 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4981 0.67757 0.704 0.108 0.000 0.000 0.188
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.6069 0.16372 0.000 0.512 0.000 0.116 0.332 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0806 0.73274 0.000 0.000 0.000 0.972 0.020 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 6 0.4587 -0.06821 0.000 0.036 0.456 0.000 0.000 0.508
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.2838 0.74546 0.000 0.004 0.000 0.808 0.188 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.3695 0.66928 0.000 0.164 0.000 0.060 0.776 0.000
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#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.1049 0.54554 0.960 0.008 0.000 0.000 0.000 0.032
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 6 0.7319 0.36706 0.168 0.000 0.000 0.156 0.276 0.400
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0146 0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4405 0.06338 0.504 0.000 0.000 0.024 0.000 0.472
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0891 0.55370 0.968 0.008 0.000 0.000 0.000 0.024
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0520 0.55937 0.984 0.008 0.000 0.000 0.000 0.008
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0622 0.77958 0.000 0.980 0.000 0.008 0.012 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 4 0.4221 0.71265 0.000 0.088 0.000 0.784 0.068 0.060
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4604 0.01052 0.536 0.432 0.000 0.008 0.000 0.024
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.4499 0.66919 0.024 0.732 0.028 0.016 0.000 0.200
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0260 0.56283 0.992 0.008 0.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0260 0.73280 0.000 0.000 0.000 0.000 0.992 0.008
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.2554 0.73370 0.000 0.876 0.000 0.048 0.000 0.076
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.5286 0.50944 0.572 0.000 0.000 0.132 0.000 0.296
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1333 0.53323 0.944 0.008 0.000 0.000 0.000 0.048
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0146 0.81419 0.000 0.000 0.996 0.000 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.5271 0.51006 0.576 0.000 0.000 0.132 0.000 0.292
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1411 0.56998 0.936 0.000 0.000 0.004 0.000 0.060
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.5855 0.48802 0.000 0.620 0.000 0.140 0.180 0.060
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.5848 0.04902 0.224 0.000 0.000 0.480 0.000 0.296
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.4481 0.42345 0.056 0.000 0.000 0.648 0.000 0.296
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3816 0.54551 0.688 0.000 0.000 0.016 0.000 0.296
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.6221 0.41726 0.000 0.304 0.000 0.124 0.520 0.052
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.5647 0.48236 0.520 0.000 0.000 0.184 0.000 0.296
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.5426 0.50145 0.556 0.000 0.000 0.152 0.000 0.292
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 6 0.5543 0.48445 0.372 0.000 0.000 0.000 0.140 0.488
#> 1122039D-5785-4F70-9916-17C585453512 3 0.0146 0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.1124 0.54266 0.956 0.008 0.000 0.000 0.000 0.036
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.6056 -0.34354 0.412 0.000 0.000 0.000 0.292 0.296
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3078 0.73980 0.000 0.012 0.000 0.796 0.192 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.1462 0.70673 0.000 0.000 0.000 0.056 0.936 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.3565 0.49666 0.000 0.692 0.000 0.004 0.000 0.304
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.2668 0.75315 0.004 0.000 0.000 0.828 0.168 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0146 0.81472 0.000 0.000 0.996 0.004 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.0000 0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0291 0.56515 0.992 0.000 0.000 0.000 0.004 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 6 0.6205 0.44738 0.176 0.044 0.232 0.000 0.000 0.548
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4066 0.49483 0.272 0.692 0.000 0.000 0.000 0.036
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 4 0.4715 0.66832 0.000 0.136 0.000 0.736 0.080 0.048
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.5611 0.48680 0.528 0.000 0.000 0.180 0.000 0.292
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.2823 0.68465 0.000 0.204 0.000 0.000 0.796 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0692 0.55418 0.976 0.004 0.000 0.000 0.000 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4895 -0.14000 0.496 0.000 0.000 0.000 0.444 0.060
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.6509 -0.33214 0.464 0.132 0.064 0.000 0.000 0.340
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 4 0.5368 0.58739 0.000 0.080 0.000 0.644 0.232 0.044
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0260 0.56622 0.992 0.000 0.000 0.000 0.000 0.008
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5684 0.22739 0.552 0.000 0.276 0.000 0.164 0.008
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.6182 0.04442 0.240 0.000 0.000 0.016 0.256 0.488
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0146 0.56516 0.996 0.000 0.000 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.2584 0.75754 0.000 0.004 0.000 0.848 0.144 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0260 0.56573 0.992 0.000 0.000 0.000 0.000 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 4 0.3732 0.73112 0.000 0.000 0.000 0.780 0.144 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.81564 0.000 0.000 1.000 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.3652 0.55272 0.000 0.324 0.000 0.004 0.672 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0806 0.55514 0.972 0.008 0.000 0.000 0.000 0.020
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.7125 0.09214 0.464 0.200 0.000 0.156 0.000 0.180
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5213 0.43103 0.488 0.000 0.000 0.092 0.000 0.420
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0622 0.56681 0.980 0.008 0.000 0.000 0.000 0.012
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.0736 0.628 0.787 0.4069 0.596 0.596
#> 3 3 0.0856 0.478 0.714 0.2945 0.898 0.835
#> 4 4 0.1500 0.336 0.592 0.2165 0.767 0.586
#> 5 5 0.2381 0.329 0.566 0.1060 0.840 0.606
#> 6 6 0.3177 0.362 0.583 0.0654 0.865 0.605
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.9977 0.15873 0.528 0.472
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0376 0.68834 0.996 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0000 0.73162 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.9833 0.37938 0.424 0.576
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.9922 0.33750 0.448 0.552
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.3879 0.77035 0.076 0.924
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9552 0.54231 0.376 0.624
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.7883 0.73561 0.236 0.764
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.2778 0.75699 0.048 0.952
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.7745 0.71461 0.228 0.772
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.8955 0.58806 0.312 0.688
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.8327 0.71350 0.264 0.736
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.7376 0.72103 0.208 0.792
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.6623 0.77486 0.172 0.828
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.9129 0.51127 0.672 0.328
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.6438 0.77192 0.164 0.836
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0376 0.68834 0.996 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.9087 0.59369 0.324 0.676
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.9998 -0.09435 0.508 0.492
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.5519 0.72805 0.128 0.872
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.9896 0.08429 0.440 0.560
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.9358 0.59727 0.352 0.648
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2778 0.70219 0.952 0.048
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.6148 0.71694 0.152 0.848
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.5842 0.69700 0.860 0.140
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.5059 0.73156 0.112 0.888
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.7453 0.75910 0.212 0.788
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.8555 0.70385 0.280 0.720
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.9977 0.21710 0.472 0.528
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 2 0.9963 0.28127 0.464 0.536
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.6801 0.76339 0.180 0.820
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.5519 0.72805 0.128 0.872
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.0376 0.68834 0.996 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 2 0.7950 0.73034 0.240 0.760
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.5408 0.77706 0.124 0.876
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.8813 0.55049 0.700 0.300
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.9358 0.45957 0.648 0.352
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 2 0.7883 0.74023 0.236 0.764
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1633 0.69588 0.976 0.024
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.0376 0.68834 0.996 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.7883 0.73823 0.236 0.764
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.9635 0.53524 0.388 0.612
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.8443 0.69186 0.272 0.728
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.1843 0.69616 0.972 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.8608 0.57206 0.716 0.284
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.2603 0.75710 0.044 0.956
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.9881 0.09694 0.436 0.564
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.8955 0.65365 0.312 0.688
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 1.0000 -0.02246 0.496 0.504
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.9754 0.45882 0.408 0.592
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 2 0.7950 0.73034 0.240 0.760
#> 4379559E-E467-49BD-9673-40A486146A3B 2 0.8955 0.64986 0.312 0.688
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.9170 0.49144 0.332 0.668
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.5059 0.77998 0.112 0.888
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.7056 0.67645 0.808 0.192
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.9323 0.47552 0.652 0.348
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.6438 0.75657 0.164 0.836
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.9522 0.38341 0.628 0.372
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.3584 0.76544 0.068 0.932
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.9323 0.57412 0.348 0.652
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#> 27CD53C1-E63D-4870-8B62-1235BF075A32 2 0.5294 0.77182 0.120 0.880
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 2 0.7883 0.74269 0.236 0.764
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.6148 0.69801 0.848 0.152
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.5178 0.76448 0.116 0.884
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.5842 0.74903 0.140 0.860
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0376 0.68834 0.996 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.5519 0.77262 0.128 0.872
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 2 0.9460 0.56674 0.364 0.636
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.5408 0.77761 0.124 0.876
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.5294 0.77078 0.120 0.880
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.5519 0.77578 0.128 0.872
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.4022 0.76925 0.080 0.920
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.4431 0.77153 0.092 0.908
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 2 0.7299 0.75902 0.204 0.796
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 2 0.9358 0.59895 0.352 0.648
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 2 0.8386 0.71025 0.268 0.732
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.9970 0.03002 0.532 0.468
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.8327 0.72088 0.264 0.736
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.6712 0.76925 0.176 0.824
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.73162 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.9909 0.17083 0.556 0.444
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.8608 0.61019 0.284 0.716
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.4815 0.76182 0.104 0.896
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.6531 0.68910 0.832 0.168
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.5737 0.78084 0.136 0.864
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.3274 0.76302 0.060 0.940
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.7139 0.67616 0.804 0.196
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 2 0.7602 0.75291 0.220 0.780
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.7376 0.64783 0.792 0.208
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1184 0.69357 0.984 0.016
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.1184 0.69357 0.984 0.016
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.5737 0.70147 0.864 0.136
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9954 0.05915 0.540 0.460
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.6887 0.68091 0.816 0.184
#> C33059A9-A313-4806-B43B-0031365F3BE4 2 0.9286 0.60297 0.344 0.656
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.4298 0.77219 0.088 0.912
#> 1122039D-5785-4F70-9916-17C585453512 1 0.3114 0.69172 0.944 0.056
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6712 0.66057 0.824 0.176
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.5737 0.77787 0.136 0.864
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9963 0.21628 0.464 0.536
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.9000 0.60973 0.316 0.684
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7139 0.75701 0.196 0.804
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.9775 0.42907 0.412 0.588
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.3114 0.69172 0.944 0.056
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.8144 0.63222 0.748 0.252
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 2 0.9209 0.62115 0.336 0.664
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.0000 0.73162 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.9710 0.48574 0.400 0.600
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 1.0000 -0.11903 0.504 0.496
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.6048 0.69804 0.852 0.148
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.9686 0.49170 0.396 0.604
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.6343 0.77198 0.160 0.840
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.9044 0.65698 0.320 0.680
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.5519 0.77617 0.128 0.872
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.5059 0.77998 0.112 0.888
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.9922 0.32611 0.448 0.552
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 2 0.7376 0.75533 0.208 0.792
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 2 0.7376 0.75533 0.208 0.792
#> EB7883EB-0079-4548-9132-169E94A698BA 2 0.8016 0.72722 0.244 0.756
#> E6446572-BFA9-4018-89B3-7E4519EBE072 2 0.9988 0.18528 0.480 0.520
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0376 0.68834 0.996 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.9977 0.03943 0.528 0.472
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.3431 0.75903 0.064 0.936
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.5294 0.74389 0.120 0.880
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.6973 0.74078 0.188 0.812
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.9358 0.60135 0.352 0.648
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.8861 0.68252 0.304 0.696
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 2 0.8327 0.70468 0.264 0.736
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.9323 0.47658 0.652 0.348
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.466 0.542479 0.068 0.856 0.076
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.148 0.619716 0.968 0.020 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.417 0.547737 0.004 0.156 0.840
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.716 0.357741 0.372 0.032 0.596
#> BE685EF3-953B-483C-A99C-75FBF81D6615 3 0.983 0.146237 0.316 0.264 0.420
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.374 0.640248 0.036 0.072 0.892
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.882 0.458593 0.296 0.148 0.556
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.530 0.640949 0.164 0.032 0.804
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.236 0.598097 0.000 0.072 0.928
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.738 0.277007 0.052 0.320 0.628
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.852 0.462723 0.096 0.508 0.396
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.621 0.631775 0.192 0.052 0.756
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 3 0.850 0.128325 0.104 0.352 0.544
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.492 0.654722 0.108 0.052 0.840
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.767 0.487529 0.620 0.068 0.312
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.353 0.658620 0.108 0.008 0.884
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.148 0.619716 0.968 0.020 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.884 0.376606 0.116 0.460 0.424
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 3 0.994 0.028835 0.344 0.284 0.372
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 3 0.704 -0.130786 0.020 0.444 0.536
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.840 0.536157 0.192 0.624 0.184
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 3 0.935 0.334490 0.224 0.260 0.516
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.504 0.629953 0.836 0.104 0.060
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 3 0.702 -0.174428 0.020 0.436 0.544
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.405 0.659611 0.848 0.004 0.148
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 3 0.685 -0.044424 0.016 0.416 0.568
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.596 0.653010 0.136 0.076 0.788
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.599 0.628687 0.208 0.036 0.756
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.781 0.258154 0.396 0.056 0.548
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.748 0.291549 0.404 0.040 0.556
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.454 0.644894 0.124 0.028 0.848
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 3 0.704 -0.130786 0.020 0.444 0.536
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.148 0.619716 0.968 0.020 0.012
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.520 0.634749 0.184 0.020 0.796
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.498 0.635904 0.064 0.096 0.840
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.777 0.501910 0.628 0.080 0.292
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.775 0.434931 0.596 0.064 0.340
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.553 0.647344 0.172 0.036 0.792
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.191 0.630041 0.956 0.016 0.028
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.148 0.619716 0.968 0.020 0.012
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.541 0.640886 0.164 0.036 0.800
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.772 0.511617 0.296 0.076 0.628
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 3 0.902 0.364536 0.176 0.276 0.548
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.584 0.551803 0.768 0.196 0.036
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.750 0.527845 0.652 0.072 0.276
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.399 0.607242 0.020 0.108 0.872
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.844 0.535740 0.192 0.620 0.188
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.641 0.606691 0.248 0.036 0.716
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.973 -0.135469 0.352 0.228 0.420
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 3 0.976 0.148184 0.268 0.288 0.444
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.520 0.634749 0.184 0.020 0.796
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.701 0.594685 0.240 0.064 0.696
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.987 -0.305113 0.256 0.356 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.550 0.642930 0.064 0.124 0.812
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.541 0.646506 0.780 0.020 0.200
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.835 0.456182 0.568 0.100 0.332
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 3 0.779 0.276085 0.068 0.332 0.600
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.857 0.354665 0.548 0.112 0.340
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.315 0.634631 0.036 0.048 0.916
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 3 0.946 0.236865 0.240 0.260 0.500
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.783 0.234357 0.404 0.056 0.540
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 3 0.877 0.401610 0.272 0.156 0.572
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.541 0.636120 0.764 0.012 0.224
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.768 0.521991 0.280 0.080 0.640
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.573 0.622733 0.228 0.020 0.752
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.337 0.644038 0.040 0.052 0.908
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.466 0.542479 0.068 0.856 0.076
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.821 0.029648 0.452 0.072 0.476
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.772 0.292243 0.396 0.052 0.552
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.667 0.429832 0.616 0.016 0.368
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.984 -0.044959 0.376 0.248 0.376
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.956 0.053573 0.444 0.356 0.200
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 3 0.640 0.528281 0.056 0.200 0.744
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.831 0.547392 0.096 0.568 0.336
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.577 0.452598 0.012 0.260 0.728
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.148 0.619716 0.968 0.020 0.012
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.346 0.619971 0.024 0.076 0.900
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.585 0.630195 0.080 0.124 0.796
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.386 0.650757 0.072 0.040 0.888
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.426 0.572696 0.012 0.140 0.848
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.794 0.437161 0.332 0.076 0.592
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.687 -0.065576 0.016 0.424 0.560
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.723 0.425187 0.600 0.036 0.364
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.346 0.591037 0.012 0.096 0.892
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.329 0.652916 0.900 0.012 0.088
#> 46351E5C-2438-4B6A-8343-DDF329086771 3 0.848 0.425564 0.140 0.260 0.600
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.504 0.656853 0.808 0.020 0.172
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.350 0.569423 0.004 0.116 0.880
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.642 0.562232 0.288 0.024 0.688
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 3 0.830 0.491358 0.152 0.220 0.628
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.525 0.632396 0.188 0.020 0.792
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.525 0.658378 0.096 0.076 0.828
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.795 0.309050 0.548 0.064 0.388
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 3 0.732 -0.096113 0.032 0.420 0.548
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.487 0.645049 0.152 0.024 0.824
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.768 0.620527 0.064 0.608 0.328
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 3 0.877 0.401610 0.272 0.156 0.572
#> 31322670-76A2-4308-A71F-D8E00049519D 3 0.707 -0.244432 0.020 0.472 0.508
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.148 0.619716 0.968 0.020 0.012
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 3 0.663 0.523979 0.064 0.204 0.732
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.525 0.632396 0.188 0.020 0.792
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.705 0.156142 0.524 0.020 0.456
#> E8327684-CDED-42F2-875C-A99E4D9E5571 3 0.868 0.476153 0.288 0.140 0.572
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.441 0.535995 0.004 0.172 0.824
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.647 0.547155 0.668 0.020 0.312
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.972 0.136011 0.448 0.252 0.300
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#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.546 0.640367 0.768 0.016 0.216
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.541 0.655353 0.156 0.040 0.804
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.879 0.471483 0.584 0.192 0.224
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.178 0.626319 0.960 0.020 0.020
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.178 0.626319 0.960 0.020 0.020
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.468 0.658548 0.832 0.020 0.148
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.986 0.062194 0.384 0.252 0.364
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.522 0.649939 0.788 0.016 0.196
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.647 0.559152 0.280 0.028 0.692
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.292 0.632018 0.032 0.044 0.924
#> 1122039D-5785-4F70-9916-17C585453512 1 0.397 0.568703 0.876 0.100 0.024
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.877 0.442981 0.588 0.200 0.212
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.514 0.631262 0.064 0.104 0.832
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.984 -0.044959 0.376 0.248 0.376
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.907 -0.319579 0.136 0.428 0.436
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.774 0.554749 0.136 0.188 0.676
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.697 0.427370 0.356 0.028 0.616
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.397 0.568703 0.876 0.100 0.024
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.620 0.597177 0.704 0.020 0.276
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.629 0.580760 0.272 0.024 0.704
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.452 0.531129 0.004 0.180 0.816
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.816 0.454155 0.320 0.092 0.588
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.926 0.080395 0.404 0.156 0.440
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.441 0.658778 0.832 0.008 0.160
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 3 0.973 0.147450 0.256 0.296 0.448
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.459 0.658235 0.120 0.032 0.848
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.715 0.590911 0.236 0.072 0.692
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.491 0.639021 0.068 0.088 0.844
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.550 0.642930 0.064 0.124 0.812
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 3 0.982 0.167378 0.324 0.256 0.420
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.527 0.652142 0.140 0.044 0.816
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.527 0.652142 0.140 0.044 0.816
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.525 0.632396 0.188 0.020 0.792
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.771 0.192690 0.424 0.048 0.528
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.148 0.619716 0.968 0.020 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.767 -0.000613 0.472 0.044 0.484
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.557 0.542990 0.032 0.184 0.784
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.691 0.237352 0.028 0.344 0.628
#> A0C429D9-0638-4873-BFB4-00056AB4719F 3 0.746 0.073750 0.048 0.352 0.600
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.709 0.551928 0.268 0.056 0.676
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.674 0.619513 0.240 0.052 0.708
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.597 0.617860 0.216 0.032 0.752
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.719 0.444439 0.608 0.036 0.356
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.431 5.69e-01 0.012 0.152 0.024 0.812
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.553 2.12e-01 0.000 0.564 0.416 0.020
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.687 3.78e-01 0.320 0.100 0.572 0.008
#> BE685EF3-953B-483C-A99C-75FBF81D6615 3 0.972 -7.38e-02 0.264 0.264 0.328 0.144
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.458 3.49e-01 0.000 0.300 0.696 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.807 2.61e-01 0.208 0.240 0.520 0.032
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.373 5.16e-01 0.056 0.092 0.852 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.515 9.64e-02 0.000 0.396 0.596 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.775 -8.51e-02 0.008 0.216 0.496 0.280
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.879 3.16e-01 0.056 0.352 0.200 0.392
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.442 5.21e-01 0.088 0.100 0.812 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.915 2.47e-01 0.076 0.372 0.316 0.236
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.451 4.49e-01 0.032 0.176 0.788 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.699 4.50e-01 0.544 0.116 0.336 0.004
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.411 4.94e-01 0.040 0.128 0.828 0.004
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.914 -2.42e-01 0.076 0.352 0.228 0.344
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 3 0.982 -1.26e-01 0.280 0.260 0.300 0.160
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.765 1.11e-01 0.000 0.460 0.236 0.304
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.783 4.90e-01 0.164 0.256 0.032 0.548
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 3 0.912 -1.31e-01 0.180 0.360 0.368 0.092
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.497 6.05e-01 0.784 0.004 0.112 0.100
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.771 1.95e-01 0.008 0.508 0.236 0.248
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.399 6.51e-01 0.800 0.008 0.188 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.753 1.96e-01 0.000 0.492 0.240 0.268
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.559 4.85e-01 0.052 0.204 0.728 0.016
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.479 5.20e-01 0.108 0.092 0.796 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.681 2.99e-01 0.292 0.088 0.604 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.628 3.41e-01 0.304 0.064 0.624 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.503 4.82e-01 0.064 0.152 0.776 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.765 1.11e-01 0.000 0.460 0.236 0.304
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.475 5.11e-01 0.100 0.088 0.804 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.547 3.96e-01 0.008 0.208 0.728 0.056
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.718 4.74e-01 0.564 0.140 0.288 0.008
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.707 4.11e-01 0.520 0.116 0.360 0.004
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.568 5.05e-01 0.112 0.124 0.748 0.016
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.193 6.17e-01 0.936 0.004 0.056 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.404 5.13e-01 0.056 0.100 0.840 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.663 4.61e-01 0.204 0.120 0.660 0.016
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.876 1.97e-01 0.132 0.412 0.368 0.088
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.613 4.82e-01 0.684 0.012 0.080 0.224
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.696 4.82e-01 0.568 0.124 0.304 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.532 1.25e-01 0.004 0.396 0.592 0.008
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.785 4.86e-01 0.164 0.260 0.032 0.544
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.581 5.07e-01 0.176 0.096 0.720 0.008
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.977 -3.97e-02 0.280 0.212 0.336 0.172
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 3 0.976 -1.27e-01 0.216 0.280 0.336 0.168
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.475 5.11e-01 0.100 0.088 0.804 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.656 4.69e-01 0.160 0.140 0.680 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.982 2.07e-01 0.256 0.288 0.160 0.296
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.531 3.46e-01 0.004 0.296 0.676 0.024
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.486 6.08e-01 0.712 0.008 0.272 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.784 4.03e-01 0.492 0.084 0.368 0.056
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.863 3.61e-01 0.048 0.408 0.352 0.192
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.781 3.52e-01 0.484 0.188 0.316 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.428 3.46e-01 0.000 0.280 0.720 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 3 0.966 -1.88e-01 0.204 0.308 0.336 0.152
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.672 2.91e-01 0.296 0.080 0.608 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 3 0.848 -7.38e-02 0.236 0.356 0.380 0.028
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.508 6.07e-01 0.700 0.028 0.272 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.657 4.49e-01 0.176 0.136 0.672 0.016
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.574 5.18e-01 0.156 0.116 0.724 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.498 3.84e-01 0.004 0.224 0.740 0.032
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.431 5.69e-01 0.012 0.152 0.024 0.812
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.741 5.59e-02 0.360 0.092 0.520 0.028
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.619 3.37e-01 0.312 0.064 0.620 0.004
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.570 3.45e-01 0.560 0.020 0.416 0.004
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 1 0.975 9.58e-03 0.360 0.228 0.236 0.176
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.941 -7.39e-02 0.368 0.136 0.168 0.328
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.681 3.14e-01 0.044 0.516 0.412 0.028
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.825 3.89e-01 0.080 0.320 0.100 0.500
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.698 2.57e-01 0.000 0.504 0.376 0.120
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.580 1.96e-01 0.012 0.340 0.624 0.024
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.640 2.70e-01 0.020 0.248 0.660 0.072
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.539 4.13e-01 0.032 0.228 0.724 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.586 -6.32e-02 0.000 0.464 0.504 0.032
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.675 4.32e-01 0.232 0.112 0.640 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.756 1.71e-01 0.000 0.484 0.236 0.280
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.665 3.48e-01 0.512 0.044 0.424 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.562 3.27e-02 0.004 0.428 0.552 0.016
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.311 6.39e-01 0.872 0.016 0.112 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.811 2.01e-01 0.100 0.456 0.384 0.060
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.427 6.36e-01 0.760 0.004 0.232 0.004
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.530 9.14e-02 0.000 0.500 0.492 0.008
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.568 4.93e-01 0.216 0.072 0.708 0.004
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 3 0.776 -1.08e-01 0.100 0.432 0.432 0.036
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.481 5.10e-01 0.104 0.088 0.800 0.008
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.474 4.73e-01 0.028 0.208 0.760 0.004
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.691 2.53e-01 0.476 0.092 0.428 0.004
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.799 1.36e-01 0.012 0.468 0.240 0.280
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.357 5.16e-01 0.048 0.092 0.860 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 4 0.770 4.93e-01 0.020 0.328 0.144 0.508
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 3 0.848 -7.38e-02 0.236 0.356 0.380 0.028
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.765 -5.85e-02 0.000 0.440 0.220 0.340
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.696 3.20e-01 0.048 0.512 0.408 0.032
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.481 5.10e-01 0.104 0.088 0.800 0.008
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.602 -6.50e-02 0.452 0.032 0.512 0.004
#> E8327684-CDED-42F2-875C-A99E4D9E5571 3 0.797 2.79e-01 0.200 0.232 0.536 0.032
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.557 2.57e-01 0.000 0.580 0.396 0.024
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.562 4.82e-01 0.600 0.016 0.376 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.932 4.61e-03 0.404 0.104 0.240 0.252
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.641 3.77e-01 0.068 0.244 0.664 0.024
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.432 5.23e-01 0.068 0.116 0.816 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.811 4.13e-01 0.028 0.468 0.332 0.172
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.630 4.79e-01 0.676 0.016 0.084 0.224
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 3 0.813 9.66e-02 0.232 0.276 0.472 0.020
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.780 3.26e-01 0.476 0.180 0.332 0.012
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.833 1.90e-01 0.116 0.444 0.376 0.064
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.732 3.77e-01 0.064 0.244 0.616 0.076
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 3 0.966 -7.91e-02 0.284 0.256 0.328 0.132
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.910 2.51e-01 0.072 0.380 0.312 0.236
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#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.402 4.59e-01 0.016 0.168 0.812 0.004
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.625 4.89e-01 0.224 0.088 0.676 0.012
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.573 3.64e-01 0.008 0.192 0.720 0.080
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.406 4.49e-01 0.016 0.172 0.808 0.004
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.514 4.10e-01 0.008 0.168 0.764 0.060
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.495 3.43e-01 0.004 0.272 0.708 0.016
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.563 2.06e-01 0.020 0.352 0.620 0.008
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.477 5.15e-01 0.068 0.116 0.804 0.012
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.561 4.87e-01 0.164 0.100 0.732 0.004
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.404 5.17e-01 0.088 0.076 0.836 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.871 2.05e-01 0.388 0.252 0.320 0.040
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.645 4.69e-01 0.144 0.156 0.684 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.388 5.16e-01 0.048 0.100 0.848 0.004
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.620 2.24e-01 0.000 0.544 0.400 0.056
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.669 1.63e-02 0.404 0.068 0.520 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 4 0.811 3.88e-01 0.020 0.348 0.192 0.440
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.667 3.37e-01 0.028 0.572 0.356 0.044
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.461 6.31e-01 0.744 0.008 0.240 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.502 4.60e-01 0.020 0.248 0.724 0.008
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.499 2.50e-01 0.004 0.344 0.648 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.503 6.04e-01 0.700 0.012 0.280 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.561 5.01e-01 0.088 0.168 0.736 0.008
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.879 4.15e-01 0.516 0.128 0.192 0.164
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.149 6.09e-01 0.956 0.004 0.036 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.149 6.09e-01 0.956 0.004 0.036 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.407 6.47e-01 0.792 0.004 0.196 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.960 1.68e-01 0.332 0.248 0.296 0.124
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.449 6.18e-01 0.732 0.004 0.260 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.638 4.97e-01 0.200 0.096 0.684 0.020
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.521 3.13e-01 0.004 0.280 0.692 0.024
#> 1122039D-5785-4F70-9916-17C585453512 1 0.345 5.32e-01 0.872 0.028 0.008 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.828 3.21e-01 0.496 0.036 0.232 0.236
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.541 3.90e-01 0.008 0.180 0.744 0.068
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.975 9.58e-03 0.360 0.228 0.236 0.176
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.935 -1.57e-01 0.088 0.332 0.272 0.308
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.771 -1.19e-01 0.096 0.428 0.440 0.036
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.612 4.50e-01 0.276 0.064 0.652 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.345 5.32e-01 0.872 0.028 0.008 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.528 5.34e-01 0.636 0.008 0.348 0.008
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.510 4.96e-01 0.184 0.056 0.756 0.004
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.614 2.19e-01 0.000 0.544 0.404 0.052
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.691 4.19e-01 0.220 0.124 0.636 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.860 -1.06e-01 0.352 0.252 0.364 0.032
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.405 6.46e-01 0.768 0.000 0.228 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 3 0.977 -1.45e-01 0.208 0.288 0.332 0.172
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.442 4.90e-01 0.032 0.184 0.784 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.599 4.81e-01 0.132 0.148 0.712 0.008
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.513 4.11e-01 0.008 0.160 0.768 0.064
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.531 3.46e-01 0.004 0.296 0.676 0.024
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 3 0.969 -6.54e-02 0.272 0.264 0.328 0.136
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.494 5.03e-01 0.060 0.108 0.804 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.494 5.03e-01 0.060 0.108 0.804 0.028
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.481 5.10e-01 0.104 0.088 0.800 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.655 2.82e-01 0.320 0.076 0.596 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.104 5.98e-01 0.972 0.008 0.020 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.670 9.98e-02 0.380 0.072 0.540 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.627 2.78e-01 0.020 0.520 0.436 0.024
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.810 2.63e-01 0.016 0.460 0.284 0.240
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.809 2.58e-01 0.032 0.508 0.276 0.184
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.578 4.79e-01 0.160 0.116 0.720 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.627 5.08e-01 0.152 0.108 0.712 0.028
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.584 4.94e-01 0.148 0.120 0.724 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.650 3.58e-01 0.520 0.036 0.424 0.020
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.576 0.62444 0.000 0.356 0.068 0.012 0.564
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.390 0.57726 0.196 0.024 0.776 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.727 0.35184 0.504 0.028 0.172 0.280 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.844 0.26624 0.256 0.408 0.040 0.232 0.064
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.548 0.04182 0.560 0.024 0.388 0.000 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.848 0.31144 0.500 0.140 0.128 0.164 0.068
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.335 0.48496 0.876 0.032 0.044 0.016 0.032
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.495 0.44023 0.396 0.024 0.576 0.000 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.808 -0.05796 0.364 0.340 0.144 0.000 0.152
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.549 0.38549 0.088 0.752 0.028 0.052 0.080
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.462 0.49785 0.808 0.032 0.076 0.048 0.036
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.668 0.51741 0.188 0.624 0.112 0.068 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.559 0.39500 0.712 0.156 0.096 0.012 0.024
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.738 0.36254 0.368 0.084 0.036 0.468 0.044
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.521 0.32637 0.692 0.036 0.244 0.012 0.016
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.621 0.41963 0.120 0.700 0.032 0.072 0.076
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.867 0.21369 0.232 0.396 0.044 0.244 0.084
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.437 0.49214 0.052 0.772 0.164 0.000 0.012
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 5 0.742 0.68588 0.000 0.128 0.296 0.092 0.484
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.942 0.25223 0.284 0.324 0.152 0.132 0.108
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.560 0.59363 0.140 0.068 0.000 0.712 0.080
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.667 0.42545 0.104 0.592 0.244 0.004 0.056
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.381 0.61695 0.200 0.012 0.004 0.780 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.506 0.49099 0.068 0.704 0.216 0.000 0.012
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.598 0.39627 0.664 0.032 0.228 0.024 0.052
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.476 0.49930 0.800 0.064 0.052 0.060 0.024
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.613 0.32118 0.644 0.012 0.036 0.236 0.072
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.563 0.39176 0.664 0.004 0.044 0.248 0.040
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.591 0.32193 0.660 0.056 0.232 0.044 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.437 0.49214 0.052 0.772 0.164 0.000 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.552 0.42393 0.740 0.044 0.128 0.064 0.024
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.641 0.28175 0.628 0.168 0.152 0.000 0.052
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.756 0.40287 0.296 0.116 0.028 0.504 0.056
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 4 0.737 0.31518 0.396 0.080 0.036 0.444 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.661 0.37629 0.628 0.052 0.220 0.076 0.024
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.193 0.61314 0.072 0.000 0.004 0.920 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.344 0.48581 0.872 0.040 0.040 0.016 0.032
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.653 0.47911 0.664 0.064 0.076 0.164 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.914 0.22193 0.300 0.332 0.192 0.100 0.076
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.660 0.44651 0.084 0.116 0.000 0.620 0.180
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.749 0.40405 0.308 0.092 0.032 0.508 0.060
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.509 0.37914 0.436 0.028 0.532 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 5 0.740 0.68346 0.000 0.124 0.300 0.092 0.484
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.620 0.48758 0.688 0.052 0.112 0.128 0.020
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.961 0.05687 0.260 0.092 0.264 0.232 0.152
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.818 0.35549 0.252 0.460 0.040 0.188 0.060
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.552 0.42393 0.740 0.044 0.128 0.064 0.024
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.665 0.42921 0.620 0.012 0.192 0.132 0.044
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.934 -0.39645 0.052 0.200 0.308 0.232 0.208
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.536 0.23150 0.612 0.004 0.320 0.000 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.465 0.54307 0.312 0.004 0.012 0.664 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.732 0.27032 0.400 0.072 0.020 0.440 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.788 0.42454 0.244 0.512 0.140 0.044 0.060
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 4 0.826 0.27277 0.300 0.168 0.040 0.428 0.064
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.519 -0.01743 0.572 0.032 0.388 0.000 0.008
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.868 0.40320 0.224 0.436 0.112 0.180 0.048
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.595 0.31393 0.648 0.008 0.028 0.240 0.076
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 1 0.927 -0.15129 0.292 0.264 0.192 0.208 0.044
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 4 0.501 0.53554 0.320 0.012 0.008 0.644 0.016
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.622 0.46394 0.700 0.032 0.076 0.116 0.076
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.634 0.46294 0.656 0.028 0.180 0.112 0.024
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.619 0.09109 0.572 0.096 0.308 0.000 0.024
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.576 0.62444 0.000 0.356 0.068 0.012 0.564
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.733 0.11671 0.532 0.044 0.044 0.296 0.084
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.537 0.36745 0.672 0.004 0.044 0.256 0.024
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 4 0.566 0.25299 0.432 0.020 0.024 0.516 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.961 -0.14656 0.108 0.236 0.184 0.316 0.156
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.952 -0.11723 0.112 0.188 0.124 0.320 0.256
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 3 0.795 0.29077 0.260 0.252 0.424 0.024 0.040
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.784 0.56467 0.008 0.208 0.348 0.056 0.380
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.603 0.52568 0.208 0.032 0.644 0.000 0.116
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.514 0.40614 0.424 0.016 0.544 0.000 0.016
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.703 0.19590 0.520 0.280 0.164 0.008 0.028
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.521 0.00836 0.580 0.020 0.384 0.008 0.008
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.498 0.54093 0.296 0.016 0.660 0.000 0.028
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.686 0.45689 0.636 0.060 0.072 0.184 0.048
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.485 0.48890 0.052 0.724 0.208 0.000 0.016
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.638 -0.22025 0.456 0.020 0.020 0.452 0.052
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.504 0.49556 0.360 0.016 0.608 0.004 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 4 0.345 0.63288 0.140 0.016 0.004 0.832 0.008
#> 46351E5C-2438-4B6A-8343-DDF329086771 1 0.912 -0.13495 0.312 0.276 0.252 0.068 0.092
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 4 0.429 0.57847 0.264 0.004 0.008 0.716 0.008
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.419 0.55422 0.260 0.016 0.720 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.598 0.44713 0.672 0.028 0.120 0.172 0.008
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 1 0.901 -0.00526 0.364 0.236 0.244 0.068 0.088
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#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.487 0.43758 0.396 0.020 0.580 0.000 0.004
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.682 0.53125 0.252 0.132 0.012 0.572 0.032
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.670 0.44254 0.092 0.116 0.000 0.612 0.180
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 1 0.924 -0.15636 0.308 0.284 0.232 0.084 0.092
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.435 0.56139 0.296 0.004 0.004 0.688 0.008
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.553 0.32689 0.676 0.020 0.244 0.044 0.016
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.547 -0.01382 0.560 0.032 0.388 0.000 0.020
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.499 0.53938 0.316 0.012 0.008 0.648 0.016
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.585 0.23136 0.604 0.024 0.312 0.056 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.588 0.36893 0.676 0.204 0.080 0.016 0.024
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.545 0.39765 0.412 0.008 0.012 0.544 0.024
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 4 0.881 0.05917 0.292 0.244 0.048 0.336 0.080
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.613 0.42974 0.340 0.032 0.044 0.572 0.012
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.704 0.45205 0.256 0.136 0.552 0.008 0.048
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.807 0.27309 0.256 0.252 0.420 0.028 0.044
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.655 -0.16327 0.480 0.036 0.024 0.420 0.040
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.915 -0.08703 0.332 0.260 0.240 0.072 0.096
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.593 0.21495 0.632 0.076 0.256 0.000 0.036
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.525 -0.11643 0.520 0.028 0.444 0.004 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.670 0.44254 0.092 0.116 0.000 0.612 0.180
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.852 0.25469 0.320 0.404 0.140 0.060 0.076
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 4 0.600 0.28528 0.440 0.008 0.020 0.488 0.044
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.610 0.47814 0.676 0.028 0.148 0.132 0.016
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.481 0.49134 0.052 0.736 0.192 0.000 0.020
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.873 0.08661 0.396 0.240 0.144 0.192 0.028
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 4 0.543 0.33658 0.440 0.012 0.012 0.520 0.016
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.568 0.30563 0.672 0.056 0.236 0.016 0.020
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.508 0.46520 0.772 0.064 0.100 0.048 0.016
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.430 0.59060 0.268 0.004 0.004 0.712 0.012
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 3 0.826 0.19343 0.308 0.236 0.372 0.024 0.060
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.666 0.51345 0.148 0.628 0.168 0.020 0.036
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.540 0.26040 0.664 0.044 0.268 0.012 0.012
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.631 0.47283 0.660 0.016 0.124 0.164 0.036
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.654 0.26944 0.612 0.204 0.124 0.000 0.060
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.549 0.25250 0.660 0.044 0.268 0.016 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.593 0.32326 0.664 0.196 0.096 0.000 0.044
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.639 -0.03185 0.532 0.096 0.344 0.000 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.530 0.31741 0.460 0.024 0.504 0.008 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.483 0.37408 0.728 0.016 0.216 0.032 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.517 0.49162 0.768 0.020 0.052 0.104 0.056
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.370 0.49666 0.860 0.032 0.032 0.048 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 4 0.871 0.07198 0.296 0.244 0.040 0.340 0.080
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.700 0.30297 0.568 0.052 0.260 0.104 0.016
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.509 0.41864 0.740 0.048 0.176 0.020 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.464 0.55993 0.180 0.020 0.752 0.000 0.048
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.603 0.09050 0.564 0.004 0.024 0.348 0.060
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.484 0.32581 0.052 0.788 0.048 0.016 0.096
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 3 0.812 0.20996 0.264 0.216 0.432 0.020 0.068
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.469 0.56624 0.280 0.004 0.012 0.688 0.016
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.542 0.33496 0.668 0.036 0.260 0.004 0.032
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.540 0.27814 0.472 0.024 0.488 0.004 0.012
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.489 0.53134 0.320 0.004 0.016 0.648 0.012
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.597 0.32050 0.632 0.024 0.272 0.056 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.850 0.35530 0.148 0.192 0.036 0.464 0.160
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.164 0.60221 0.048 0.000 0.008 0.940 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.164 0.60221 0.048 0.000 0.008 0.940 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.407 0.61273 0.232 0.004 0.008 0.748 0.008
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.876 0.09599 0.232 0.348 0.036 0.288 0.096
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.461 0.55382 0.284 0.004 0.016 0.688 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.647 0.44542 0.636 0.024 0.160 0.160 0.020
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.637 -0.18130 0.484 0.084 0.408 0.004 0.020
#> 1122039D-5785-4F70-9916-17C585453512 4 0.358 0.50721 0.012 0.000 0.048 0.840 0.100
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.872 0.28300 0.212 0.128 0.044 0.432 0.184
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.624 0.29614 0.640 0.196 0.112 0.000 0.052
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.961 -0.14656 0.108 0.236 0.184 0.316 0.156
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.648 0.42617 0.168 0.664 0.028 0.076 0.064
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.884 0.15670 0.320 0.176 0.356 0.064 0.084
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.649 0.45379 0.628 0.040 0.084 0.228 0.020
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.358 0.50721 0.012 0.000 0.048 0.840 0.100
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.503 0.45167 0.388 0.004 0.012 0.584 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.559 0.47370 0.732 0.048 0.056 0.140 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.448 0.55691 0.192 0.012 0.752 0.000 0.044
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.711 0.44814 0.624 0.080 0.080 0.168 0.048
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.881 -0.12807 0.320 0.248 0.064 0.308 0.060
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.425 0.59444 0.260 0.004 0.004 0.720 0.012
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.818 0.37978 0.248 0.468 0.044 0.180 0.060
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.448 0.38952 0.744 0.020 0.216 0.008 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.575 0.47628 0.740 0.040 0.080 0.076 0.064
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.611 0.31398 0.652 0.188 0.112 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.536 0.23150 0.612 0.004 0.320 0.000 0.064
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.852 0.25513 0.256 0.396 0.044 0.240 0.064
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.504 0.44241 0.776 0.088 0.080 0.020 0.036
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.504 0.44241 0.776 0.088 0.080 0.020 0.036
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.550 0.42391 0.740 0.044 0.128 0.068 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.622 0.30450 0.616 0.004 0.052 0.264 0.064
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.128 0.58810 0.020 0.000 0.004 0.960 0.016
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.624 0.15571 0.576 0.008 0.028 0.320 0.068
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.703 0.49152 0.248 0.160 0.548 0.012 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.659 0.23983 0.112 0.060 0.616 0.004 0.208
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.664 0.46832 0.152 0.604 0.204 0.012 0.028
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.530 0.48828 0.764 0.032 0.048 0.100 0.056
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.677 0.46957 0.640 0.072 0.152 0.116 0.020
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.624 0.39389 0.656 0.044 0.184 0.108 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 4 0.630 0.22720 0.452 0.016 0.020 0.460 0.052
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.626 4.34e-01 0.000 0.092 0.052 0.432 0.420 0.004
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.155 6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.274 5.99e-01 0.072 0.028 0.880 0.016 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.680 3.83e-01 0.492 0.044 0.164 0.008 0.008 0.284
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.684 3.79e-01 0.136 0.568 0.000 0.036 0.084 0.176
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.574 1.29e-02 0.480 0.060 0.424 0.016 0.020 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.800 5.36e-02 0.404 0.312 0.116 0.040 0.024 0.104
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.342 5.61e-01 0.860 0.024 0.048 0.012 0.040 0.016
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.369 5.60e-01 0.288 0.012 0.700 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.744 8.73e-02 0.320 0.076 0.144 0.040 0.420 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.622 -3.00e-01 0.052 0.448 0.016 0.012 0.436 0.036
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.460 5.73e-01 0.792 0.044 0.076 0.016 0.036 0.036
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.726 2.66e-01 0.128 0.508 0.056 0.008 0.252 0.048
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.577 4.63e-01 0.680 0.128 0.096 0.004 0.076 0.016
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.700 3.18e-01 0.280 0.228 0.000 0.036 0.020 0.436
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.484 3.64e-01 0.648 0.020 0.292 0.008 0.032 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.155 6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.683 -2.02e-01 0.080 0.432 0.020 0.012 0.400 0.056
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.714 3.63e-01 0.124 0.544 0.000 0.056 0.088 0.188
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.606 -3.43e-02 0.016 0.508 0.136 0.008 0.332 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.487 6.49e-01 0.000 0.024 0.124 0.748 0.056 0.048
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.695 4.71e-01 0.144 0.604 0.104 0.040 0.024 0.084
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.555 5.92e-01 0.132 0.004 0.004 0.028 0.176 0.656
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.751 5.13e-02 0.036 0.444 0.228 0.060 0.228 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.352 6.39e-01 0.184 0.024 0.000 0.008 0.000 0.784
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.658 1.86e-02 0.020 0.464 0.188 0.016 0.312 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.625 4.56e-01 0.620 0.080 0.208 0.052 0.036 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.483 5.70e-01 0.768 0.068 0.072 0.004 0.028 0.060
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.645 4.08e-01 0.628 0.052 0.020 0.048 0.060 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.608 4.80e-01 0.644 0.032 0.052 0.020 0.044 0.208
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.552 3.52e-01 0.628 0.016 0.276 0.008 0.028 0.044
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.606 -3.43e-02 0.016 0.508 0.136 0.008 0.332 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 6 0.155 6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.497 4.98e-01 0.744 0.016 0.132 0.008 0.040 0.060
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.659 3.56e-01 0.572 0.092 0.156 0.012 0.168 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 6 0.663 2.08e-01 0.204 0.308 0.000 0.036 0.004 0.448
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 6 0.715 2.83e-01 0.312 0.220 0.000 0.040 0.024 0.404
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.607 4.19e-01 0.604 0.060 0.252 0.008 0.012 0.064
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.163 6.44e-01 0.060 0.000 0.000 0.012 0.000 0.928
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.155 6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.351 5.62e-01 0.856 0.032 0.044 0.012 0.040 0.016
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.669 5.33e-01 0.616 0.116 0.084 0.028 0.016 0.140
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.708 4.91e-01 0.168 0.556 0.172 0.036 0.016 0.052
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.574 4.15e-01 0.068 0.000 0.012 0.028 0.336 0.556
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 6 0.663 2.54e-01 0.232 0.284 0.000 0.032 0.004 0.448
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.466 5.03e-01 0.308 0.028 0.644 0.016 0.004 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.491 6.49e-01 0.000 0.024 0.128 0.744 0.056 0.048
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.578 5.51e-01 0.676 0.076 0.124 0.004 0.012 0.108
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.921 -1.19e-03 0.204 0.044 0.292 0.076 0.192 0.192
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.678 3.66e-01 0.132 0.592 0.004 0.032 0.100 0.140
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.497 4.98e-01 0.744 0.016 0.132 0.008 0.040 0.060
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.713 4.89e-01 0.572 0.040 0.196 0.048 0.040 0.104
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.884 3.56e-01 0.028 0.160 0.212 0.340 0.064 0.196
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#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.521 5.46e-01 0.728 0.024 0.068 0.008 0.036 0.136
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.404 5.46e-01 0.080 0.028 0.808 0.068 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.727 4.77e-01 0.564 0.160 0.084 0.032 0.028 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.717 3.41e-01 0.208 0.472 0.028 0.024 0.016 0.252
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.404 5.94e-01 0.264 0.012 0.000 0.004 0.012 0.708
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.669 3.64e-01 0.128 0.600 0.004 0.028 0.108 0.132
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.454 4.55e-01 0.692 0.020 0.260 0.008 0.012 0.008
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.607 5.44e-01 0.700 0.084 0.048 0.056 0.052 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.637 3.91e-01 0.604 0.092 0.112 0.016 0.176 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.653 2.83e-01 0.532 0.068 0.304 0.056 0.040 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.696 3.87e-01 0.136 0.564 0.008 0.028 0.080 0.184
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.496 5.20e-01 0.756 0.064 0.088 0.008 0.068 0.016
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.496 5.20e-01 0.756 0.064 0.088 0.008 0.068 0.016
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.495 4.98e-01 0.744 0.016 0.132 0.008 0.036 0.064
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.664 3.94e-01 0.600 0.040 0.036 0.044 0.056 0.224
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.155 6.12e-01 0.004 0.032 0.000 0.012 0.008 0.944
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.657 2.57e-01 0.560 0.044 0.016 0.044 0.052 0.284
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.613 3.05e-01 0.120 0.256 0.580 0.020 0.020 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.575 1.15e-01 0.048 0.024 0.572 0.324 0.032 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.743 9.60e-02 0.104 0.476 0.168 0.012 0.228 0.012
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.539 5.56e-01 0.744 0.068 0.028 0.044 0.040 0.076
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.647 5.32e-01 0.632 0.092 0.136 0.012 0.024 0.104
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.568 4.48e-01 0.648 0.016 0.212 0.008 0.020 0.096
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.648 -1.50e-01 0.448 0.060 0.008 0.028 0.040 0.416
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.410 0.740 0.860 0.4908 0.503 0.503
#> 3 3 0.680 0.824 0.896 0.3304 0.640 0.402
#> 4 4 0.558 0.655 0.780 0.1066 0.807 0.526
#> 5 5 0.623 0.576 0.757 0.0701 0.920 0.739
#> 6 6 0.643 0.506 0.702 0.0478 0.853 0.501
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0672 0.7906 0.008 0.992
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.7602 0.7226 0.780 0.220
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.7674 0.7710 0.224 0.776
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.7528 0.7342 0.784 0.216
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.9866 0.4616 0.568 0.432
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.8763 0.7408 0.296 0.704
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5737 0.6757 0.136 0.864
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0672 0.8586 0.992 0.008
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.8763 0.7408 0.296 0.704
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.8813 0.7426 0.300 0.700
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0672 0.7906 0.008 0.992
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.6531 0.6797 0.832 0.168
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0376 0.7922 0.004 0.996
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.9608 0.6106 0.384 0.616
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.7528 0.7264 0.784 0.216
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.8763 0.7408 0.296 0.704
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.7745 0.7245 0.772 0.228
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.7940 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.9993 0.3253 0.516 0.484
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.7940 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.1843 0.7904 0.028 0.972
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.7940 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8560 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.7940 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1414 0.8551 0.980 0.020
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.7940 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.8763 0.7408 0.296 0.704
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0672 0.8586 0.992 0.008
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0672 0.8586 0.992 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0672 0.8586 0.992 0.008
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.9815 0.5620 0.420 0.580
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.7940 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.7745 0.7245 0.772 0.228
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.5737 0.7284 0.864 0.136
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.8763 0.7408 0.296 0.704
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.7674 0.7237 0.776 0.224
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.8955 0.6340 0.688 0.312
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0672 0.8586 0.992 0.008
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0672 0.8586 0.992 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.7815 0.7210 0.768 0.232
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3114 0.8221 0.944 0.056
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0672 0.8586 0.992 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.7940 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8560 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.7745 0.7245 0.772 0.228
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.8763 0.7408 0.296 0.704
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.7940 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0672 0.8586 0.992 0.008
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 0.8861 0.7395 0.304 0.696
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.7602 0.5444 0.220 0.780
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0672 0.8586 0.992 0.008
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.7674 0.5735 0.776 0.224
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0376 0.7924 0.004 0.996
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.8763 0.7408 0.296 0.704
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0672 0.8586 0.992 0.008
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.3879 0.8216 0.924 0.076
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.7940 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.8813 0.6459 0.700 0.300
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.8763 0.7408 0.296 0.704
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.9522 0.1419 0.372 0.628
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0672 0.8586 0.992 0.008
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2778 0.7638 0.048 0.952
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0672 0.8586 0.992 0.008
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.8560 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.9850 -0.1591 0.572 0.428
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.8813 0.7403 0.300 0.700
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0672 0.7906 0.008 0.992
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.8560 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0672 0.8586 0.992 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0672 0.8586 0.992 0.008
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.7940 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7139 0.6865 0.196 0.804
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.7940 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.7940 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.7602 0.7719 0.220 0.780
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.7745 0.7245 0.772 0.228
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.8763 0.7408 0.296 0.704
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0672 0.7906 0.008 0.992
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.9896 0.5202 0.440 0.560
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.7602 0.7719 0.220 0.780
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0672 0.8586 0.992 0.008
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.7940 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0672 0.8586 0.992 0.008
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.7602 0.7719 0.220 0.780
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.3274 0.8333 0.940 0.060
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.7940 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0672 0.8586 0.992 0.008
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.7815 0.7688 0.232 0.768
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0672 0.8586 0.992 0.008
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.7940 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0672 0.8586 0.992 0.008
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.8763 0.7408 0.296 0.704
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0376 0.8575 0.996 0.004
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.7940 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0672 0.8586 0.992 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0672 0.7906 0.008 0.992
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.9323 0.2237 0.348 0.652
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0672 0.7906 0.008 0.992
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.7745 0.7245 0.772 0.228
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.7940 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0672 0.8586 0.992 0.008
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0672 0.8586 0.992 0.008
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.6247 0.7860 0.156 0.844
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.7940 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0672 0.8586 0.992 0.008
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.9850 0.5427 0.428 0.572
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#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.8813 0.7367 0.300 0.700
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3114 0.8220 0.944 0.056
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.8861 0.7395 0.304 0.696
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.8763 0.7408 0.296 0.704
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.9552 0.1276 0.376 0.624
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.8560 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.8560 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0672 0.8586 0.992 0.008
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0672 0.8586 0.992 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.7674 0.7237 0.776 0.224
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0672 0.8586 0.992 0.008
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.7940 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.6343 0.7859 0.160 0.840
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.7940 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.8560 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0938 0.8578 0.988 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0672 0.8586 0.992 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0672 0.8586 0.992 0.008
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.2982 0.8634 0.024 0.920 0.056
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2584 0.8678 0.928 0.064 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1163 0.8987 0.000 0.028 0.972
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.2651 0.8721 0.928 0.060 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.6600 0.3751 0.384 0.604 0.012
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0592 0.9050 0.000 0.012 0.988
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.6154 0.7151 0.204 0.752 0.044
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.3038 0.8727 0.104 0.000 0.896
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0747 0.9045 0.000 0.016 0.984
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2879 0.8872 0.024 0.052 0.924
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.1170 0.8743 0.016 0.976 0.008
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.2711 0.8822 0.088 0.000 0.912
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1765 0.8977 0.004 0.956 0.040
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.4339 0.8602 0.048 0.084 0.868
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.2313 0.8862 0.944 0.032 0.024
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0237 0.9058 0.000 0.004 0.996
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.2749 0.8699 0.924 0.064 0.012
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.1765 0.8977 0.004 0.956 0.040
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2651 0.8485 0.060 0.928 0.012
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.1529 0.8983 0.000 0.960 0.040
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.6511 0.7341 0.180 0.748 0.072
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1765 0.8977 0.004 0.956 0.040
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0592 0.8870 0.988 0.000 0.012
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1529 0.8983 0.000 0.960 0.040
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1031 0.8916 0.976 0.000 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.2625 0.8838 0.000 0.916 0.084
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.1399 0.9042 0.028 0.004 0.968
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.6204 0.2818 0.424 0.000 0.576
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5016 0.7223 0.240 0.000 0.760
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.2796 0.8802 0.092 0.000 0.908
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.1015 0.9059 0.008 0.012 0.980
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1529 0.8983 0.000 0.960 0.040
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.2749 0.8699 0.924 0.064 0.012
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.2625 0.8843 0.084 0.000 0.916
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.0592 0.9054 0.000 0.012 0.988
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.2879 0.8784 0.924 0.052 0.024
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.6686 0.3736 0.612 0.372 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.2878 0.8797 0.096 0.000 0.904
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1163 0.8918 0.972 0.000 0.028
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.2749 0.8699 0.924 0.064 0.012
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.2959 0.8754 0.100 0.000 0.900
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.2796 0.8802 0.092 0.000 0.908
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1529 0.8983 0.000 0.960 0.040
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.2116 0.8729 0.948 0.040 0.012
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.2982 0.8766 0.920 0.056 0.024
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0747 0.9045 0.000 0.016 0.984
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.3918 0.8439 0.004 0.856 0.140
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.5810 0.5354 0.336 0.000 0.664
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.3267 0.8879 0.044 0.044 0.912
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0829 0.8768 0.004 0.984 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.4796 0.7593 0.220 0.000 0.780
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.2625 0.8842 0.084 0.000 0.916
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.1905 0.8913 0.016 0.956 0.028
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.0592 0.9050 0.000 0.012 0.988
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1411 0.8922 0.964 0.000 0.036
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1482 0.8818 0.968 0.020 0.012
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1529 0.8983 0.000 0.960 0.040
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6813 0.1136 0.468 0.520 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0747 0.9045 0.000 0.016 0.984
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.1765 0.8977 0.004 0.956 0.040
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.5327 0.6584 0.272 0.000 0.728
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1765 0.8977 0.004 0.956 0.040
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3340 0.8508 0.880 0.000 0.120
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.6598 0.2587 0.428 0.008 0.564
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.4449 0.8625 0.100 0.040 0.860
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.2280 0.8948 0.008 0.052 0.940
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.1453 0.8713 0.024 0.968 0.008
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3610 0.8453 0.888 0.096 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.2796 0.8802 0.092 0.000 0.908
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1411 0.8922 0.964 0.000 0.036
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.2116 0.8954 0.012 0.948 0.040
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.4121 0.8102 0.108 0.868 0.024
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1529 0.8983 0.000 0.960 0.040
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.3116 0.8702 0.000 0.892 0.108
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.1163 0.8987 0.000 0.028 0.972
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.2749 0.8699 0.924 0.064 0.012
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0747 0.9045 0.000 0.016 0.984
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.2096 0.8756 0.004 0.944 0.052
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1315 0.9056 0.020 0.008 0.972
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1163 0.8987 0.000 0.028 0.972
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.6309 0.0237 0.504 0.000 0.496
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.2448 0.8877 0.000 0.924 0.076
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.3038 0.8634 0.896 0.000 0.104
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.1163 0.8987 0.000 0.028 0.972
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1163 0.8922 0.972 0.000 0.028
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1643 0.8981 0.000 0.956 0.044
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1411 0.8922 0.964 0.000 0.036
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0892 0.9029 0.000 0.020 0.980
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.6192 0.3032 0.420 0.000 0.580
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1643 0.8981 0.000 0.956 0.044
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.3116 0.8721 0.108 0.000 0.892
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.0592 0.9050 0.000 0.012 0.988
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.4235 0.7934 0.824 0.000 0.176
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.1765 0.8977 0.004 0.956 0.040
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.3038 0.8727 0.104 0.000 0.896
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.1453 0.8713 0.024 0.968 0.008
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1878 0.8971 0.004 0.952 0.044
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0747 0.8853 0.000 0.984 0.016
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.2749 0.8699 0.924 0.064 0.012
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1529 0.8983 0.000 0.960 0.040
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.5706 0.5563 0.680 0.000 0.320
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.4002 0.8051 0.840 0.000 0.160
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.6095 0.4738 0.000 0.608 0.392
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.2796 0.8795 0.000 0.908 0.092
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.4178 0.7973 0.828 0.000 0.172
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5901 0.7592 0.176 0.048 0.776
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.4589 0.8041 0.820 0.008 0.172
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0747 0.9054 0.016 0.000 0.984
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1529 0.8983 0.000 0.960 0.040
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.1950 0.8720 0.952 0.040 0.008
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6701 0.2982 0.412 0.576 0.012
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.7207 0.3686 0.384 0.584 0.032
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1643 0.8981 0.000 0.956 0.044
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.3583 0.8854 0.056 0.044 0.900
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.6735 0.2098 0.424 0.564 0.012
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.1529 0.8983 0.000 0.960 0.040
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.2773 0.8868 0.024 0.048 0.928
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1860 0.8958 0.000 0.948 0.052
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0592 0.9053 0.000 0.012 0.988
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.3042 0.8672 0.920 0.040 0.040
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.3043 0.8897 0.084 0.008 0.908
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1289 0.8921 0.968 0.000 0.032
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.6007 0.7396 0.184 0.768 0.048
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.4379 0.8651 0.060 0.072 0.868
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.2743 0.8664 0.020 0.928 0.052
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.1999 0.8828 0.952 0.036 0.012
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.6600 0.3535 0.604 0.384 0.012
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.0983 0.9059 0.016 0.004 0.980
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.1529 0.8918 0.960 0.000 0.040
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.6713 0.2997 0.416 0.572 0.012
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.2711 0.8822 0.088 0.000 0.912
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0237 0.8819 0.004 0.996 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0592 0.9053 0.000 0.012 0.988
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.1129 0.9052 0.020 0.004 0.976
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1529 0.8918 0.960 0.000 0.040
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0747 0.9045 0.000 0.016 0.984
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.2749 0.8699 0.924 0.064 0.012
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.2537 0.8866 0.000 0.920 0.080
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.1411 0.8922 0.964 0.000 0.036
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.1860 0.8959 0.000 0.948 0.052
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0747 0.9045 0.000 0.016 0.984
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.0747 0.9045 0.000 0.016 0.984
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.1643 0.8981 0.000 0.956 0.044
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.2356 0.8895 0.000 0.928 0.072
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 3 0.3826 0.8666 0.124 0.008 0.868
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.2711 0.8818 0.000 0.912 0.088
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.1529 0.8983 0.000 0.960 0.040
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.4602 0.8202 0.852 0.040 0.108
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0747 0.9045 0.000 0.016 0.984
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.1163 0.8918 0.972 0.000 0.028
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.2796 0.8795 0.000 0.908 0.092
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.0747 0.9045 0.000 0.016 0.984
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 3 0.0892 0.9029 0.000 0.020 0.980
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#> F8E9F501-DECA-4A6A-8CF1-1A54915E6FA6 2 0.2773 0.8666 0.024 0.928 0.048
#> B3AFCDBB-95EF-4028-84F7-9DBC39B25E70 2 0.1529 0.8983 0.000 0.960 0.040
#> 864ACE9F-29B4-4BB2-A966-E6F601637A79 2 0.1529 0.8983 0.000 0.960 0.040
#> 932BAFF1-A2A8-404F-A9E9-44DCAA8CFF83 1 0.1031 0.8916 0.976 0.000 0.024
#> 1C82688E-01A7-4723-8266-F614FB7EABE5 3 0.4178 0.8136 0.172 0.000 0.828
#> 8FED16FD-AFBF-475D-A19F-1BC84D0AA571 3 0.0747 0.9040 0.000 0.016 0.984
#> 9EF7685F-CA09-4869-94EA-12A1129093B1 2 0.2796 0.8795 0.000 0.908 0.092
#> 18AB08E8-6C1A-49E4-9DF0-79D80D9BEC78 3 0.1163 0.8987 0.000 0.028 0.972
#> 97FB3176-395F-475B-8EAE-332C5BEE8155 3 0.5692 0.7942 0.176 0.040 0.784
#> E1876307-DFD9-4688-876F-D71B37466068 2 0.2625 0.8838 0.000 0.916 0.084
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04 2 0.6081 0.5606 0.004 0.652 0.344
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00 1 0.2749 0.8699 0.924 0.064 0.012
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79 3 0.0747 0.9040 0.000 0.016 0.984
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 3 0.0592 0.9050 0.000 0.012 0.988
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 1 0.6168 0.3331 0.588 0.000 0.412
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 3 0.0592 0.9053 0.000 0.012 0.988
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 3 0.0892 0.9029 0.000 0.020 0.980
#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.1163 0.8918 0.972 0.000 0.028
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 3 0.6449 0.7463 0.056 0.204 0.740
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 3 0.0829 0.9057 0.004 0.012 0.984
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.1643 0.8981 0.000 0.956 0.044
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 3 0.2356 0.8911 0.072 0.000 0.928
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.2356 0.8895 0.000 0.928 0.072
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.1529 0.8983 0.000 0.960 0.040
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 3 0.3941 0.7798 0.000 0.156 0.844
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 3 0.1877 0.9014 0.012 0.032 0.956
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.2356 0.8895 0.000 0.928 0.072
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.4702 0.7500 0.788 0.000 0.212
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.0747 0.9045 0.000 0.016 0.984
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.0747 0.9045 0.000 0.016 0.984
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.3039 0.8878 0.036 0.044 0.920
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.6126 0.3573 0.600 0.000 0.400
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.2261 0.8908 0.000 0.932 0.068
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.2625 0.8838 0.000 0.916 0.084
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.5058 0.7060 0.756 0.000 0.244
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.1453 0.8713 0.024 0.968 0.008
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.1163 0.8987 0.000 0.028 0.972
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.1411 0.8922 0.964 0.000 0.036
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.1529 0.8983 0.000 0.960 0.040
#> 457090A2-AE7F-4E68-85EA-032DE8411110 3 0.4178 0.8140 0.172 0.000 0.828
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0424 0.9054 0.000 0.008 0.992
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.1529 0.8919 0.960 0.000 0.040
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.1765 0.8977 0.004 0.956 0.040
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.2584 0.8952 0.064 0.008 0.928
#> 34ED910C-7470-4552-8561-D01D59190521 3 0.5346 0.8178 0.152 0.040 0.808
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.1163 0.8987 0.000 0.028 0.972
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.2749 0.8699 0.924 0.064 0.012
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.1453 0.8713 0.024 0.968 0.008
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.1529 0.8983 0.000 0.960 0.040
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.0747 0.9045 0.000 0.016 0.984
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.7475 0.3759 0.376 0.580 0.044
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.5798 0.7531 0.176 0.780 0.044
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.6380 0.6886 0.224 0.732 0.044
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.3083 0.8743 0.916 0.060 0.024
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.2796 0.8795 0.000 0.908 0.092
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.1411 0.8922 0.964 0.000 0.036
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.1163 0.8918 0.972 0.000 0.028
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.2796 0.8802 0.092 0.000 0.908
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.1529 0.8919 0.960 0.000 0.040
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.1163 0.8987 0.000 0.028 0.972
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.6423 0.6824 0.228 0.728 0.044
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.1620 0.8701 0.024 0.964 0.012
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.2356 0.8895 0.000 0.928 0.072
#> 80936433-AA91-4219-98F1-706C36298060 2 0.1529 0.8983 0.000 0.960 0.040
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.2384 0.8731 0.936 0.056 0.008
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.5330 0.8252 0.044 0.144 0.812
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.6111 0.3722 0.396 0.000 0.604
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.2116 0.8729 0.948 0.040 0.012
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.2356 0.8894 0.000 0.928 0.072
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.2711 0.8822 0.088 0.000 0.912
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.1411 0.8922 0.964 0.000 0.036
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.2261 0.8831 0.932 0.000 0.068
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.4842 0.7320 0.776 0.000 0.224
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.3482 0.8449 0.872 0.000 0.128
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0592 0.9053 0.000 0.012 0.988
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0747 0.9045 0.000 0.016 0.984
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.2749 0.8699 0.924 0.064 0.012
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.3695 0.8438 0.880 0.108 0.012
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.2116 0.8729 0.948 0.040 0.012
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.1643 0.8981 0.000 0.956 0.044
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.1411 0.8922 0.964 0.000 0.036
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.2486 0.8981 0.060 0.008 0.932
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0592 0.9050 0.000 0.012 0.988
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.1529 0.8919 0.960 0.000 0.040
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.2955 0.8900 0.080 0.008 0.912
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.6302 0.6968 0.048 0.208 0.744
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.1411 0.8922 0.964 0.000 0.036
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.6724 0.2745 0.420 0.568 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.1636 0.8896 0.964 0.016 0.020
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.2878 0.8778 0.000 0.904 0.096
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.1765 0.8977 0.004 0.956 0.040
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.3038 0.8634 0.896 0.000 0.104
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.1643 0.8981 0.000 0.956 0.044
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0747 0.9045 0.000 0.016 0.984
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0747 0.9045 0.000 0.016 0.984
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.2116 0.8729 0.948 0.040 0.012
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1643 0.8981 0.000 0.956 0.044
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.2749 0.8699 0.924 0.064 0.012
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.3482 0.8441 0.872 0.000 0.128
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.1832 0.9032 0.036 0.008 0.956
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.2356 0.8895 0.000 0.928 0.072
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.7263 0.4087 0.372 0.592 0.036
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.4931 0.7187 0.768 0.000 0.232
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2261 0.8920 0.068 0.000 0.932
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.3481 0.8881 0.052 0.044 0.904
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.1411 0.8922 0.964 0.000 0.036
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1529 0.8983 0.000 0.960 0.040
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.1529 0.8983 0.000 0.960 0.040
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2749 0.8699 0.924 0.064 0.012
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0592 0.9053 0.000 0.012 0.988
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.4887 0.7281 0.772 0.000 0.228
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.2383 0.8912 0.016 0.044 0.940
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0747 0.9045 0.000 0.016 0.984
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.3263 0.8879 0.048 0.040 0.912
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0747 0.9045 0.000 0.016 0.984
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0892 0.9029 0.000 0.020 0.980
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.2866 0.8917 0.076 0.008 0.916
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.2796 0.8802 0.092 0.000 0.908
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.3038 0.8727 0.104 0.000 0.896
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.6490 0.3992 0.360 0.628 0.012
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.4802 0.7707 0.156 0.020 0.824
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.2550 0.8937 0.024 0.040 0.936
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.4682 0.7308 0.004 0.192 0.804
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.3038 0.8634 0.896 0.000 0.104
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0829 0.8775 0.012 0.984 0.004
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1529 0.8983 0.000 0.960 0.040
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1411 0.8922 0.964 0.000 0.036
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.1753 0.8994 0.048 0.000 0.952
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0747 0.9045 0.000 0.016 0.984
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.1411 0.8922 0.964 0.000 0.036
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.2537 0.8862 0.080 0.000 0.920
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6510 0.4091 0.364 0.624 0.012
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1620 0.8864 0.964 0.024 0.012
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.2116 0.8811 0.948 0.040 0.012
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.1411 0.8922 0.964 0.000 0.036
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.4861 0.7335 0.180 0.808 0.012
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.1411 0.8922 0.964 0.000 0.036
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.1529 0.8918 0.960 0.000 0.040
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0592 0.9053 0.000 0.012 0.988
#> 1122039D-5785-4F70-9916-17C585453512 1 0.2486 0.8690 0.932 0.060 0.008
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 3 0.5524 0.8094 0.164 0.040 0.796
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.2173 0.8943 0.008 0.048 0.944
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.3752 0.8057 0.144 0.856 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0848 0.8765 0.008 0.984 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.4504 0.7878 0.000 0.804 0.196
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.6307 0.0535 0.512 0.000 0.488
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.2486 0.8690 0.932 0.060 0.008
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.1643 0.8910 0.956 0.000 0.044
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.4605 0.7800 0.204 0.000 0.796
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0747 0.9045 0.000 0.016 0.984
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.6498 0.3329 0.396 0.008 0.596
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1878 0.8971 0.004 0.952 0.044
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.1411 0.8922 0.964 0.000 0.036
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5268 0.6766 0.212 0.776 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1453 0.9054 0.024 0.008 0.968
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.2959 0.8754 0.100 0.000 0.900
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.3042 0.8887 0.040 0.040 0.920
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0592 0.9050 0.000 0.012 0.988
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1878 0.8971 0.004 0.952 0.044
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.4136 0.8569 0.116 0.020 0.864
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.4449 0.8615 0.100 0.040 0.860
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.4399 0.7997 0.188 0.000 0.812
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3116 0.8605 0.892 0.000 0.108
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.2749 0.8699 0.924 0.064 0.012
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.5560 0.6031 0.700 0.000 0.300
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5529 0.6455 0.000 0.704 0.296
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3784 0.8109 0.004 0.132 0.864
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1529 0.8983 0.000 0.960 0.040
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.3752 0.8719 0.096 0.020 0.884
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.5678 0.5751 0.316 0.000 0.684
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.3213 0.8862 0.092 0.008 0.900
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2796 0.8714 0.908 0.000 0.092
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.6006 0.71147 0.096 0.700 0.008 0.196
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1256 0.84301 0.000 0.008 0.964 0.028
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4198 0.84228 0.224 0.004 0.004 0.768
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.5565 0.56438 0.056 0.684 0.000 0.260
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2032 0.83893 0.036 0.000 0.936 0.028
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4599 0.71962 0.088 0.800 0.000 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4382 0.66704 0.704 0.000 0.296 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0779 0.84884 0.016 0.004 0.980 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4130 0.72869 0.108 0.000 0.828 0.064
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3836 0.80703 0.028 0.840 0.004 0.128
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4967 0.44963 0.548 0.000 0.452 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2589 0.82101 0.000 0.884 0.000 0.116
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7653 0.48717 0.512 0.204 0.276 0.008
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.5244 0.59245 0.436 0.008 0.000 0.556
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.2530 0.76578 0.112 0.000 0.888 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.2704 0.81850 0.000 0.876 0.000 0.124
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.4889 0.61670 0.000 0.636 0.004 0.360
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.7974 0.01131 0.040 0.368 0.120 0.472
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2011 0.82391 0.000 0.920 0.000 0.080
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.3649 0.37429 0.796 0.000 0.000 0.204
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2408 0.82128 0.000 0.896 0.000 0.104
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.5168 -0.48673 0.500 0.000 0.004 0.496
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.3105 0.81717 0.000 0.868 0.012 0.120
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.6290 -0.27491 0.476 0.016 0.480 0.028
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4387 0.70293 0.752 0.012 0.236 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4898 0.67881 0.716 0.000 0.260 0.024
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4477 0.64707 0.688 0.000 0.312 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.1716 0.82515 0.064 0.000 0.936 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4948 0.46877 0.560 0.000 0.440 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.0895 0.84529 0.020 0.004 0.976 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.5784 0.58740 0.412 0.032 0.000 0.556
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5511 0.37334 0.636 0.332 0.000 0.032
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4941 0.44565 0.564 0.000 0.436 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.5028 0.67158 0.400 0.000 0.004 0.596
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4643 0.62750 0.656 0.000 0.344 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4454 0.64332 0.692 0.000 0.308 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0188 0.82332 0.000 0.996 0.000 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.4188 0.38477 0.752 0.000 0.004 0.244
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.5856 0.58725 0.408 0.036 0.000 0.556
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0376 0.84924 0.000 0.004 0.992 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.7143 0.22626 0.000 0.460 0.408 0.132
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.4283 0.69090 0.740 0.000 0.256 0.004
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.7147 0.43064 0.564 0.020 0.320 0.096
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2593 0.82200 0.000 0.892 0.004 0.104
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.4283 0.69407 0.740 0.000 0.256 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.5681 0.02094 0.404 0.000 0.568 0.028
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.4916 0.47546 0.000 0.576 0.000 0.424
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.2570 0.83130 0.052 0.004 0.916 0.028
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.2944 0.54602 0.868 0.000 0.004 0.128
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.4304 0.18673 0.716 0.000 0.000 0.284
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.82356 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6356 0.39387 0.088 0.604 0.000 0.308
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0524 0.84865 0.008 0.004 0.988 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.3975 0.74976 0.000 0.760 0.000 0.240
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.4103 0.69408 0.744 0.000 0.256 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0921 0.81997 0.000 0.972 0.000 0.028
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3953 0.65246 0.860 0.028 0.072 0.040
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4365 0.71629 0.784 0.000 0.188 0.028
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.5937 0.49075 0.608 0.000 0.340 0.052
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.0469 0.84820 0.012 0.000 0.988 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5788 0.72005 0.088 0.708 0.004 0.200
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3301 0.60378 0.876 0.028 0.004 0.092
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4585 0.62039 0.668 0.000 0.332 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3052 0.53186 0.860 0.000 0.004 0.136
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.4697 0.60659 0.000 0.644 0.000 0.356
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7391 0.18073 0.400 0.464 0.008 0.128
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0336 0.82321 0.000 0.992 0.000 0.008
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.7098 0.27050 0.000 0.472 0.400 0.128
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.2066 0.83445 0.008 0.024 0.940 0.028
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1443 0.84276 0.008 0.004 0.960 0.028
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.4205 0.79183 0.004 0.832 0.096 0.068
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.3032 0.77924 0.124 0.000 0.868 0.008
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1721 0.83995 0.008 0.012 0.952 0.028
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5883 0.68123 0.736 0.108 0.136 0.020
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.2831 0.81815 0.000 0.876 0.004 0.120
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.3845 0.66023 0.864 0.048 0.068 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.1749 0.84516 0.012 0.012 0.952 0.024
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.5155 -0.41307 0.528 0.000 0.004 0.468
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0921 0.81952 0.000 0.972 0.000 0.028
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.4283 0.29824 0.740 0.000 0.004 0.256
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0188 0.84898 0.000 0.004 0.996 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.4436 0.70715 0.764 0.000 0.216 0.020
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1109 0.81861 0.004 0.968 0.000 0.028
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4770 0.67217 0.700 0.000 0.288 0.012
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.2385 0.83232 0.052 0.000 0.920 0.028
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.4337 0.66719 0.836 0.072 0.076 0.016
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.4431 0.65672 0.696 0.000 0.304 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.5763 0.72155 0.084 0.708 0.004 0.204
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3444 0.74560 0.000 0.816 0.000 0.184
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.2831 0.81765 0.000 0.876 0.004 0.120
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0188 0.82396 0.000 0.996 0.000 0.004
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.4365 0.70392 0.784 0.000 0.188 0.028
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.3447 0.68777 0.852 0.000 0.128 0.020
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.3881 0.76815 0.040 0.864 0.068 0.028
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.3796 0.80758 0.000 0.848 0.056 0.096
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.3708 0.69681 0.832 0.000 0.148 0.020
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5555 0.64856 0.140 0.004 0.740 0.116
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.6856 0.63580 0.284 0.000 0.140 0.576
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.2704 0.76272 0.124 0.000 0.876 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.2408 0.82147 0.000 0.896 0.000 0.104
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.5080 -0.19107 0.576 0.000 0.004 0.420
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6517 0.37599 0.288 0.604 0.000 0.108
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.5247 0.60235 0.052 0.720 0.000 0.228
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1109 0.81861 0.004 0.968 0.000 0.028
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.6240 0.49520 0.604 0.000 0.320 0.076
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.6547 0.37801 0.084 0.588 0.004 0.324
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.2469 0.82074 0.000 0.892 0.000 0.108
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.3734 0.74667 0.108 0.000 0.848 0.044
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.82356 0.000 1.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0779 0.84884 0.016 0.004 0.980 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.2593 0.60059 0.892 0.000 0.004 0.104
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.3123 0.72132 0.156 0.000 0.844 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.3355 0.50034 0.836 0.000 0.004 0.160
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.4197 0.70883 0.036 0.808 0.000 0.156
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.7042 0.36525 0.516 0.000 0.352 0.132
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.5284 0.75911 0.068 0.756 0.008 0.168
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.4053 0.84060 0.228 0.000 0.004 0.768
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.7335 0.11154 0.488 0.344 0.000 0.168
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.6073 0.32217 0.496 0.008 0.468 0.028
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.3108 0.57466 0.872 0.000 0.016 0.112
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 4 0.4467 0.73126 0.104 0.076 0.004 0.816
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.4977 0.43488 0.540 0.000 0.460 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.2831 0.81765 0.000 0.876 0.004 0.120
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0779 0.84884 0.016 0.004 0.980 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.4830 0.06174 0.392 0.000 0.608 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.2635 0.66096 0.904 0.000 0.076 0.020
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0524 0.84910 0.000 0.004 0.988 0.008
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.4442 0.61931 0.004 0.752 0.236 0.008
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.3105 0.53105 0.856 0.000 0.004 0.140
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0779 0.84884 0.016 0.004 0.980 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.2944 0.76090 0.128 0.004 0.868 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0469 0.82265 0.000 0.988 0.000 0.012
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0921 0.81952 0.000 0.972 0.000 0.028
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.5398 0.49636 0.580 0.000 0.404 0.016
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.1209 0.82040 0.000 0.964 0.004 0.032
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.2662 0.60855 0.900 0.000 0.016 0.084
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0524 0.84865 0.008 0.004 0.988 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 4 0.4950 0.70730 0.376 0.000 0.004 0.620
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.2988 0.81871 0.000 0.876 0.012 0.112
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.0188 0.84898 0.000 0.004 0.996 0.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 3 0.0376 0.84909 0.004 0.004 0.992 0.000
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.4155 0.38453 0.756 0.000 0.004 0.240
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 1 0.7018 0.22519 0.492 0.008 0.408 0.092
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.2654 0.59334 0.888 0.000 0.004 0.108
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.2714 0.68791 0.884 0.000 0.112 0.004
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 1 0.6055 0.29221 0.520 0.000 0.436 0.044
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F 2 0.7146 0.28507 0.212 0.560 0.000 0.228
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0 2 0.1109 0.81861 0.004 0.968 0.000 0.028
#> D149276E-A961-49D6-8BDA-004E8264A0A1 1 0.4843 0.53785 0.604 0.000 0.396 0.000
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#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4993 0.68056 0.712 0.000 0.260 0.028
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5272 0.66198 0.680 0.000 0.288 0.032
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4606 0.69196 0.724 0.000 0.264 0.012
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3015 0.67065 0.884 0.000 0.092 0.024
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4163 0.84425 0.220 0.004 0.004 0.772
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3653 0.68921 0.844 0.000 0.128 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.5466 0.48027 0.000 0.292 0.668 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2282 0.82488 0.000 0.024 0.924 0.052
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2647 0.81838 0.000 0.880 0.000 0.120
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5022 0.68064 0.708 0.000 0.264 0.028
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5515 0.70647 0.728 0.052 0.208 0.012
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4220 0.57865 0.248 0.000 0.748 0.004
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2949 0.66783 0.888 0.000 0.088 0.024
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.4534 0.329475 0.028 0.224 0.000 0.016 0.732
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1741 0.814755 0.000 0.024 0.936 0.000 0.040
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0932 0.835943 0.020 0.004 0.000 0.972 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3519 0.555158 0.008 0.776 0.000 0.216 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4817 0.767750 0.060 0.024 0.760 0.004 0.152
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.3846 0.556951 0.080 0.840 0.040 0.004 0.036
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4558 0.684212 0.740 0.000 0.080 0.000 0.180
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0324 0.819640 0.004 0.000 0.992 0.000 0.004
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.5236 0.356033 0.048 0.000 0.544 0.000 0.408
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.4302 0.357343 0.000 0.520 0.000 0.000 0.480
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5454 0.611881 0.672 0.000 0.148 0.004 0.176
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.4549 0.379785 0.000 0.528 0.000 0.008 0.464
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7996 0.192662 0.436 0.196 0.128 0.000 0.240
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6529 0.069884 0.456 0.172 0.000 0.368 0.004
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.3927 0.761462 0.040 0.000 0.792 0.004 0.164
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.5974 0.404408 0.000 0.548 0.000 0.320 0.132
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6483 0.348208 0.000 0.172 0.024 0.580 0.224
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3003 0.576796 0.000 0.812 0.000 0.000 0.188
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.3857 0.643092 0.808 0.000 0.000 0.084 0.108
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.4415 0.392705 0.000 0.552 0.000 0.004 0.444
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.4118 0.433004 0.660 0.000 0.000 0.336 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.4648 0.369260 0.000 0.524 0.012 0.000 0.464
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.7099 0.450195 0.560 0.072 0.232 0.004 0.132
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4838 0.708605 0.768 0.016 0.072 0.012 0.132
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2540 0.732328 0.904 0.004 0.036 0.004 0.052
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3826 0.710431 0.812 0.000 0.056 0.004 0.128
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.3507 0.762731 0.052 0.000 0.828 0.000 0.120
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.5440 0.613575 0.660 0.000 0.184 0.000 0.156
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.3812 0.765642 0.036 0.000 0.800 0.004 0.160
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.6804 -0.040164 0.404 0.232 0.000 0.360 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5120 0.254922 0.540 0.428 0.000 0.008 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4905 0.637314 0.696 0.000 0.224 0.000 0.080
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.4298 0.508546 0.352 0.000 0.000 0.640 0.008
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4914 0.661505 0.712 0.000 0.108 0.000 0.180
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.3550 0.728675 0.848 0.008 0.080 0.004 0.060
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0404 0.640171 0.000 0.988 0.000 0.000 0.012
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.5409 0.378632 0.612 0.000 0.000 0.084 0.304
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6884 -0.028397 0.396 0.268 0.000 0.332 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1205 0.821209 0.000 0.000 0.956 0.004 0.040
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6322 0.181324 0.000 0.144 0.532 0.008 0.316
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3037 0.731225 0.860 0.000 0.100 0.000 0.040
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.8369 0.148041 0.300 0.104 0.192 0.016 0.388
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.4262 0.400578 0.000 0.560 0.000 0.000 0.440
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.4886 0.685650 0.744 0.000 0.124 0.012 0.120
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.6107 0.511699 0.620 0.020 0.248 0.004 0.108
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.6059 0.320773 0.000 0.184 0.000 0.572 0.244
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5074 0.755888 0.080 0.028 0.748 0.004 0.140
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.2300 0.722034 0.904 0.000 0.000 0.072 0.024
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2956 0.693037 0.848 0.004 0.000 0.140 0.008
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0703 0.639067 0.000 0.976 0.000 0.000 0.024
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4468 0.505617 0.044 0.716 0.000 0.240 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.3340 0.792150 0.032 0.000 0.840 0.004 0.124
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.6121 0.347881 0.000 0.464 0.000 0.128 0.408
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.2673 0.730966 0.892 0.000 0.044 0.004 0.060
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1571 0.631592 0.000 0.936 0.000 0.060 0.004
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.1461 0.730585 0.952 0.028 0.000 0.016 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.2331 0.733482 0.912 0.004 0.020 0.004 0.060
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.7132 -0.154267 0.356 0.004 0.368 0.008 0.264
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.2843 0.787362 0.008 0.000 0.848 0.000 0.144
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.4353 0.326748 0.024 0.224 0.000 0.012 0.740
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3462 0.619950 0.792 0.000 0.000 0.012 0.196
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3142 0.728125 0.864 0.000 0.076 0.004 0.056
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3038 0.718482 0.872 0.000 0.016 0.088 0.024
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.6237 0.253913 0.000 0.196 0.000 0.540 0.264
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7687 -0.124243 0.164 0.408 0.040 0.020 0.368
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0324 0.640215 0.000 0.992 0.000 0.004 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.6558 -0.032656 0.000 0.156 0.448 0.008 0.388
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3149 0.806693 0.012 0.032 0.872 0.004 0.080
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1978 0.813425 0.000 0.024 0.928 0.004 0.044
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.5864 0.328273 0.004 0.536 0.092 0.000 0.368
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.3372 0.765226 0.104 0.008 0.852 0.004 0.032
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.2125 0.812922 0.000 0.024 0.920 0.004 0.052
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5216 0.387649 0.604 0.344 0.000 0.004 0.048
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.2321 0.724009 0.916 0.044 0.000 0.016 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.1074 0.818429 0.004 0.016 0.968 0.000 0.012
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.3928 0.509598 0.700 0.000 0.000 0.296 0.004
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0566 0.636950 0.004 0.984 0.000 0.000 0.012
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.2624 0.703637 0.872 0.000 0.000 0.116 0.012
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0963 0.821076 0.000 0.000 0.964 0.000 0.036
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.3561 0.735958 0.852 0.000 0.068 0.028 0.052
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1960 0.620315 0.012 0.936 0.028 0.004 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4788 0.681086 0.740 0.000 0.136 0.004 0.120
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.4817 0.766507 0.084 0.028 0.772 0.004 0.112
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.2267 0.724599 0.916 0.048 0.000 0.008 0.028
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.4417 0.689412 0.760 0.000 0.092 0.000 0.148
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.3835 0.298529 0.012 0.244 0.000 0.000 0.744
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3242 0.584533 0.000 0.816 0.000 0.172 0.012
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0794 0.638760 0.000 0.972 0.000 0.000 0.028
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.4919 0.700079 0.756 0.000 0.100 0.028 0.116
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.2523 0.736563 0.908 0.000 0.040 0.024 0.028
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.3630 0.563433 0.032 0.852 0.076 0.004 0.036
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.5995 0.256118 0.000 0.468 0.112 0.000 0.420
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.2444 0.736561 0.912 0.000 0.036 0.028 0.024
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.5783 0.357106 0.040 0.016 0.604 0.016 0.324
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.5016 0.619830 0.076 0.000 0.184 0.724 0.016
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.4545 0.739014 0.084 0.000 0.756 0.004 0.156
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.4262 0.399511 0.000 0.560 0.000 0.000 0.440
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.6374 0.233855 0.504 0.000 0.000 0.196 0.300
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.5503 0.453060 0.184 0.712 0.020 0.064 0.020
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.3555 0.574128 0.052 0.824 0.000 0.124 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0727 0.636987 0.004 0.980 0.000 0.004 0.012
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.6923 0.345818 0.516 0.028 0.120 0.012 0.324
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.4323 0.449661 0.012 0.656 0.000 0.332 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.5771 0.294039 0.076 0.000 0.500 0.004 0.420
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1059 0.641111 0.000 0.968 0.008 0.004 0.020
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0324 0.819640 0.004 0.000 0.992 0.000 0.004
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.4401 0.406936 0.656 0.000 0.000 0.016 0.328
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.3016 0.735970 0.132 0.000 0.848 0.000 0.020
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.2761 0.709083 0.872 0.000 0.000 0.104 0.024
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.2416 0.610749 0.012 0.888 0.000 0.100 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 5 0.5391 0.383201 0.108 0.000 0.192 0.012 0.688
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 5 0.3612 0.241081 0.000 0.268 0.000 0.000 0.732
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.5479 -0.028479 0.452 0.500 0.000 0.032 0.016
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.6519 0.524074 0.608 0.032 0.180 0.004 0.176
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.2760 0.727100 0.892 0.000 0.016 0.064 0.028
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 4 0.1455 0.808681 0.008 0.008 0.000 0.952 0.032
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.5789 0.583527 0.632 0.000 0.172 0.004 0.192
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.4291 0.383533 0.000 0.536 0.000 0.000 0.464
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0566 0.819928 0.004 0.000 0.984 0.000 0.012
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.6339 0.377554 0.512 0.000 0.328 0.004 0.156
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1978 0.733478 0.932 0.000 0.012 0.032 0.024
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.1197 0.821275 0.000 0.000 0.952 0.000 0.048
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#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0566 0.819322 0.004 0.000 0.984 0.000 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.5991 0.554562 0.616 0.000 0.172 0.008 0.204
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.2886 0.789423 0.008 0.000 0.844 0.000 0.148
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0324 0.819640 0.004 0.000 0.992 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.3238 0.754989 0.136 0.000 0.836 0.000 0.028
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4019 0.701025 0.792 0.000 0.052 0.004 0.152
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3506 0.719358 0.824 0.000 0.044 0.000 0.132
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.3012 0.591977 0.024 0.852 0.000 0.124 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3241 0.747166 0.036 0.100 0.856 0.000 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.6684 -0.084272 0.352 0.000 0.408 0.000 0.240
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.3123 0.797714 0.004 0.040 0.876 0.012 0.068
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.1667 0.734341 0.948 0.012 0.012 0.004 0.024
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4306 0.338593 0.000 0.508 0.000 0.000 0.492
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0613 0.637642 0.004 0.984 0.000 0.004 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2338 0.706431 0.884 0.000 0.000 0.112 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.6068 0.559831 0.632 0.012 0.176 0.004 0.176
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2873 0.794515 0.016 0.000 0.856 0.000 0.128
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2300 0.721852 0.904 0.000 0.000 0.072 0.024
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.3495 0.728924 0.160 0.000 0.812 0.000 0.028
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.7198 0.127004 0.040 0.476 0.000 0.192 0.292
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0609 0.837972 0.020 0.000 0.000 0.980 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0609 0.837972 0.020 0.000 0.000 0.980 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.2597 0.714385 0.884 0.000 0.000 0.092 0.024
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.7507 -0.000529 0.036 0.340 0.000 0.272 0.352
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.2540 0.715980 0.888 0.000 0.000 0.088 0.024
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.1830 0.723068 0.924 0.000 0.000 0.068 0.008
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.2727 0.786631 0.016 0.000 0.868 0.000 0.116
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0566 0.837952 0.012 0.004 0.000 0.984 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6430 0.148697 0.448 0.000 0.112 0.016 0.424
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.4289 0.725624 0.064 0.000 0.760 0.000 0.176
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.1756 0.799868 0.008 0.016 0.000 0.940 0.036
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.5648 0.350980 0.000 0.476 0.000 0.076 0.448
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5480 0.102146 0.016 0.548 0.400 0.000 0.036
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.3671 0.732638 0.844 0.000 0.060 0.024 0.072
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0566 0.837952 0.012 0.004 0.000 0.984 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.1978 0.731431 0.928 0.000 0.004 0.044 0.024
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4025 0.700923 0.792 0.000 0.076 0.000 0.132
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2285 0.812631 0.004 0.024 0.916 0.004 0.052
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5563 0.251490 0.512 0.432 0.004 0.004 0.048
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2339 0.613555 0.004 0.892 0.000 0.100 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.3224 0.670845 0.824 0.000 0.000 0.160 0.016
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.6091 0.448477 0.000 0.560 0.000 0.172 0.268
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4139 0.750216 0.052 0.000 0.780 0.004 0.164
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4703 0.671135 0.744 0.000 0.096 0.004 0.156
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.6677 0.057656 0.328 0.000 0.212 0.004 0.456
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4492 0.782890 0.048 0.028 0.788 0.004 0.132
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3488 0.585551 0.000 0.808 0.000 0.168 0.024
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4283 0.696930 0.780 0.000 0.080 0.004 0.136
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5038 0.664482 0.716 0.000 0.128 0.004 0.152
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4930 0.682838 0.740 0.000 0.128 0.012 0.120
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1612 0.735333 0.948 0.000 0.012 0.016 0.024
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0671 0.840676 0.016 0.004 0.000 0.980 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.2067 0.735784 0.924 0.000 0.028 0.004 0.044
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.2387 0.779674 0.004 0.048 0.908 0.000 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2521 0.806489 0.000 0.024 0.900 0.008 0.068
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.4287 0.386439 0.000 0.540 0.000 0.000 0.460
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3209 0.720858 0.848 0.000 0.028 0.004 0.120
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6806 0.460512 0.568 0.272 0.080 0.004 0.076
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4848 0.640708 0.176 0.000 0.736 0.012 0.076
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1997 0.733022 0.936 0.012 0.008 0.020 0.024
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.4510 0.405394 0.000 0.024 0.004 0.004 0.600 0.368
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0291 0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2987 0.741780 0.088 0.020 0.864 0.000 0.020 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1401 0.842822 0.004 0.000 0.020 0.948 0.000 0.028
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3722 0.690688 0.000 0.764 0.000 0.196 0.004 0.036
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.4384 -0.370689 0.520 0.016 0.460 0.000 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.2129 0.764593 0.056 0.904 0.000 0.000 0.000 0.040
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2094 0.436219 0.908 0.000 0.008 0.000 0.016 0.068
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0436 0.742423 0.004 0.004 0.988 0.000 0.004 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.7068 0.260111 0.328 0.000 0.376 0.000 0.080 0.216
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3046 0.873997 0.000 0.188 0.000 0.000 0.800 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.1503 0.454564 0.944 0.000 0.032 0.000 0.008 0.016
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.3133 0.876276 0.000 0.212 0.000 0.000 0.780 0.008
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7804 0.262979 0.452 0.068 0.144 0.000 0.228 0.108
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.6996 0.163600 0.068 0.256 0.000 0.276 0.000 0.400
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.4815 -0.269265 0.532 0.000 0.424 0.000 0.012 0.032
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0291 0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.3133 0.876276 0.000 0.212 0.000 0.000 0.780 0.008
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.6663 -0.043564 0.000 0.388 0.000 0.312 0.268 0.032
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.2854 0.879174 0.000 0.208 0.000 0.000 0.792 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6344 0.403826 0.000 0.052 0.024 0.536 0.312 0.076
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2431 0.706155 0.000 0.860 0.000 0.000 0.132 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.3968 0.456357 0.148 0.008 0.000 0.048 0.012 0.784
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.4227 0.794861 0.000 0.256 0.000 0.000 0.692 0.052
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.5879 0.447935 0.228 0.004 0.000 0.260 0.000 0.508
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.3417 0.848760 0.000 0.160 0.044 0.000 0.796 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.3141 0.438346 0.852 0.040 0.084 0.000 0.000 0.024
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.5201 0.305581 0.644 0.000 0.112 0.000 0.016 0.228
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3816 0.075343 0.688 0.016 0.000 0.000 0.000 0.296
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2500 0.382727 0.868 0.012 0.004 0.000 0.000 0.116
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4185 0.597125 0.168 0.000 0.752 0.000 0.012 0.068
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.2854 0.879174 0.000 0.208 0.000 0.000 0.792 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0146 0.875508 0.004 0.000 0.000 0.996 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.5378 0.402912 0.632 0.000 0.232 0.000 0.024 0.112
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4939 0.438466 0.456 0.000 0.496 0.000 0.024 0.024
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 6 0.7025 0.104514 0.064 0.288 0.000 0.280 0.000 0.368
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4750 0.536061 0.100 0.656 0.000 0.000 0.000 0.244
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.6149 0.249311 0.448 0.000 0.308 0.000 0.008 0.236
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.4876 0.203523 0.048 0.004 0.000 0.444 0.000 0.504
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.874345 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.2613 0.442461 0.884 0.000 0.032 0.000 0.016 0.068
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.5129 0.282105 0.668 0.020 0.120 0.000 0.000 0.192
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0858 0.790516 0.000 0.968 0.000 0.000 0.028 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.4893 0.404917 0.108 0.004 0.000 0.040 0.120 0.728
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.7160 0.183632 0.088 0.388 0.000 0.256 0.000 0.268
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3013 0.733220 0.152 0.004 0.828 0.000 0.012 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.5848 0.340336 0.000 0.032 0.532 0.008 0.352 0.076
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5659 -0.038893 0.488 0.000 0.164 0.000 0.000 0.348
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.6725 0.210510 0.520 0.068 0.080 0.000 0.036 0.296
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.3420 0.848720 0.000 0.240 0.000 0.000 0.748 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5812 0.235224 0.564 0.000 0.156 0.000 0.020 0.260
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.4024 0.405220 0.792 0.032 0.100 0.000 0.000 0.076
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.5632 0.467417 0.000 0.056 0.000 0.588 0.292 0.064
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.4755 -0.362546 0.512 0.024 0.452 0.000 0.004 0.008
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.4310 0.439832 0.440 0.000 0.000 0.020 0.000 0.540
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.5200 0.459846 0.296 0.008 0.000 0.084 0.004 0.608
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1082 0.786332 0.000 0.956 0.000 0.000 0.040 0.004
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3803 0.694364 0.000 0.760 0.000 0.184 0.000 0.056
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.4370 0.508634 0.428 0.000 0.552 0.000 0.012 0.008
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.4885 0.787912 0.000 0.204 0.000 0.096 0.684 0.016
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3534 0.195374 0.740 0.016 0.000 0.000 0.000 0.244
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1882 0.788495 0.000 0.928 0.000 0.028 0.020 0.024
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.4195 0.409118 0.440 0.008 0.004 0.000 0.000 0.548
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.3674 0.152768 0.716 0.016 0.000 0.000 0.000 0.268
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.6729 0.041442 0.160 0.004 0.436 0.000 0.056 0.344
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.4512 0.622482 0.272 0.000 0.676 0.000 0.028 0.024
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.4185 0.459852 0.000 0.020 0.000 0.004 0.644 0.332
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 6 0.4780 0.253765 0.364 0.016 0.000 0.000 0.032 0.588
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4695 0.052620 0.624 0.012 0.040 0.000 0.000 0.324
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.5619 0.381240 0.412 0.000 0.056 0.032 0.004 0.496
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5816 0.398075 0.000 0.068 0.000 0.556 0.316 0.060
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.6386 0.267909 0.028 0.440 0.004 0.004 0.136 0.388
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0777 0.791718 0.000 0.972 0.000 0.000 0.024 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.5642 0.228858 0.000 0.020 0.492 0.004 0.408 0.076
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.5146 0.678325 0.232 0.024 0.676 0.000 0.028 0.040
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0291 0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.3235 0.736661 0.124 0.016 0.836 0.000 0.016 0.008
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.7244 0.545786 0.092 0.200 0.144 0.000 0.520 0.044
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1987 0.732228 0.080 0.004 0.908 0.000 0.004 0.004
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.3755 0.724327 0.152 0.028 0.796 0.000 0.016 0.008
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5721 -0.008936 0.520 0.240 0.000 0.000 0.000 0.240
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.3078 0.873899 0.000 0.192 0.012 0.000 0.796 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.4254 -0.135951 0.576 0.020 0.000 0.000 0.000 0.404
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.1425 0.744664 0.012 0.008 0.952 0.000 0.020 0.008
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#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.4289 0.424353 0.444 0.004 0.000 0.012 0.000 0.540
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#> F7849C4C-5733-40C6-A826-EF610E7CB14E 6 0.6675 -0.030016 0.376 0.012 0.040 0.004 0.128 0.440
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.5249 0.361971 0.444 0.000 0.488 0.000 0.032 0.036
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.1003 0.860618 0.000 0.004 0.000 0.964 0.028 0.004
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#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0458 0.870339 0.000 0.000 0.000 0.984 0.016 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.4304 0.417882 0.448 0.000 0.008 0.008 0.000 0.536
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#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3718 0.725589 0.148 0.028 0.800 0.000 0.016 0.008
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.5119 0.499375 0.220 0.624 0.000 0.000 0.000 0.156
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1930 0.787708 0.000 0.924 0.000 0.036 0.012 0.028
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.5001 0.470398 0.384 0.000 0.000 0.076 0.000 0.540
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.6005 0.514871 0.000 0.328 0.000 0.124 0.516 0.032
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4029 0.231643 0.688 0.000 0.288 0.000 0.012 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.1116 0.438960 0.960 0.004 0.008 0.000 0.000 0.028
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.6119 0.306935 0.572 0.000 0.116 0.000 0.068 0.244
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5111 -0.395374 0.492 0.024 0.456 0.000 0.012 0.016
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3721 0.709585 0.000 0.784 0.000 0.168 0.016 0.032
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4686 0.328106 0.700 0.000 0.068 0.000 0.020 0.212
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5393 0.369223 0.656 0.000 0.160 0.000 0.032 0.152
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.6009 0.266284 0.548 0.000 0.192 0.000 0.024 0.236
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4199 -0.204258 0.568 0.016 0.000 0.000 0.000 0.416
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0291 0.876033 0.004 0.000 0.000 0.992 0.000 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4088 -0.080215 0.616 0.016 0.000 0.000 0.000 0.368
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.1719 0.741762 0.000 0.008 0.928 0.000 0.056 0.008
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.5127 0.706350 0.116 0.024 0.732 0.000 0.056 0.072
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.2994 0.878568 0.000 0.208 0.000 0.000 0.788 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2805 0.332002 0.828 0.012 0.000 0.000 0.000 0.160
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6550 0.087343 0.452 0.348 0.064 0.000 0.000 0.136
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5789 -0.020864 0.316 0.000 0.516 0.000 0.008 0.160
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.4224 -0.238381 0.552 0.016 0.000 0.000 0.000 0.432
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.815 0.879 0.947 0.5008 0.499 0.499
#> 3 3 0.861 0.885 0.952 0.3334 0.675 0.438
#> 4 4 0.688 0.700 0.857 0.1197 0.838 0.567
#> 5 5 0.652 0.323 0.655 0.0653 0.865 0.544
#> 6 6 0.722 0.577 0.777 0.0418 0.850 0.426
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 3
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.9446 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.1633 0.9323 0.976 0.024
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.1633 0.9423 0.024 0.976
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.1633 0.9323 0.976 0.024
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.4815 0.8684 0.896 0.104
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.1633 0.9423 0.024 0.976
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.8443 0.6081 0.272 0.728
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9401 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.1633 0.9423 0.024 0.976
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.1633 0.9423 0.024 0.976
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.9446 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.6801 0.7559 0.820 0.180
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9446 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.7815 0.7120 0.232 0.768
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.1633 0.9323 0.976 0.024
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.1633 0.9423 0.024 0.976
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.1633 0.9323 0.976 0.024
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9446 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.8386 0.6506 0.732 0.268
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9446 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.9446 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9446 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9401 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9446 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1633 0.9323 0.976 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9446 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.1633 0.9423 0.024 0.976
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.9401 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.9401 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9401 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.9988 0.1198 0.480 0.520
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9446 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.1633 0.9323 0.976 0.024
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.3584 0.8877 0.932 0.068
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.1633 0.9423 0.024 0.976
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.1633 0.9323 0.976 0.024
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.1633 0.9323 0.976 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.9401 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9401 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.1633 0.9323 0.976 0.024
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0938 0.9339 0.988 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.9401 1.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9446 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9401 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.1633 0.9323 0.976 0.024
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.1633 0.9423 0.024 0.976
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.9446 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.9401 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 0.7674 0.7215 0.224 0.776
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.6712 0.7608 0.176 0.824
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9401 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3274 0.8954 0.940 0.060
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.9446 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.1633 0.9423 0.024 0.976
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9401 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.1633 0.9323 0.976 0.024
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9446 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.1633 0.9323 0.976 0.024
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.1633 0.9423 0.024 0.976
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.9833 0.2340 0.424 0.576
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.9401 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2043 0.9240 0.032 0.968
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9401 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.9401 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6531 0.7761 0.832 0.168
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.1633 0.9423 0.024 0.976
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.9446 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.9401 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.9401 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.9401 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.9446 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.7376 0.7206 0.208 0.792
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.9446 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.9446 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.1633 0.9423 0.024 0.976
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.1633 0.9323 0.976 0.024
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.1633 0.9423 0.024 0.976
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0000 0.9446 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.9170 0.4950 0.668 0.332
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.1633 0.9423 0.024 0.976
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.9401 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.9446 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.9401 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.1633 0.9423 0.024 0.976
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.1414 0.9338 0.980 0.020
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.9446 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9401 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.1633 0.9423 0.024 0.976
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.9401 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.9446 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.9401 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.1633 0.9423 0.024 0.976
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0000 0.9401 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.9446 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.9401 1.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0000 0.9446 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.9815 0.2466 0.420 0.580
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.9446 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.1633 0.9323 0.976 0.024
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.9446 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.9401 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.9401 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0000 0.9446 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.9446 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0000 0.9401 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.7883 0.7044 0.236 0.764
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.1633 0.9323 0.976 0.024
#> AE903797-7FFB-44A1-B834-C644784B5DC2 2 0.8386 0.6466 0.268 0.732
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.9446 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.1633 0.9323 0.976 0.024
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.4022 0.8917 0.920 0.080
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.6343 0.8064 0.840 0.160
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.9446 0.000 1.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.9896 0.1980 0.560 0.440
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.1633 0.9323 0.976 0.024
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.9446 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 2 0.1633 0.9423 0.024 0.976
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.9446 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 2 0.1633 0.9423 0.024 0.976
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.9401 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0000 0.9401 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.9401 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 1 0.8661 0.6171 0.712 0.288
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 2 0.5519 0.8475 0.128 0.872
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0000 0.9446 0.000 1.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.1633 0.9323 0.976 0.024
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.1633 0.9323 0.976 0.024
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 2 0.1633 0.9423 0.024 0.976
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.9401 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.7376 0.7251 0.208 0.792
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.6623 0.7669 0.828 0.172
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.9446 0.000 1.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 2 0.1633 0.9423 0.024 0.976
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 2 0.1633 0.9423 0.024 0.976
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.0000 0.9401 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 2 0.1633 0.9423 0.024 0.976
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.1633 0.9323 0.976 0.024
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.9446 0.000 1.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.0000 0.9401 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.9446 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 2 0.1633 0.9423 0.024 0.976
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 2 0.1633 0.9423 0.024 0.976
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.9446 0.000 1.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.9446 0.000 1.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.0000 0.9401 1.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.9446 0.000 1.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.9446 0.000 1.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0000 0.9401 1.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 2 0.1633 0.9423 0.024 0.976
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.0000 0.9401 1.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.9446 0.000 1.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 2 0.1633 0.9423 0.024 0.976
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 2 0.1633 0.9423 0.024 0.976
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.0000 0.9401 1.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 2 0.1633 0.9423 0.024 0.976
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.0000 0.9401 1.000 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.0000 0.9401 1.000 0.000
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 2 0.9795 0.3108 0.416 0.584
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#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 2 0.8016 0.6994 0.244 0.756
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.0000 0.9446 0.000 1.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.0938 0.9341 0.988 0.012
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.9446 0.000 1.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.9446 0.000 1.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.1633 0.9423 0.024 0.976
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 2 0.8608 0.6206 0.284 0.716
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.9446 0.000 1.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.0000 0.9401 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 2 0.1633 0.9423 0.024 0.976
#> 985FEEC2-9737-4018-80DF-21A07AB47900 2 0.1633 0.9423 0.024 0.976
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 2 0.9491 0.4398 0.368 0.632
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.0000 0.9401 1.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9446 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.9446 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.0000 0.9401 1.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.0000 0.9446 0.000 1.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.1633 0.9423 0.024 0.976
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0000 0.9401 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.9446 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.9401 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 2 0.7219 0.7581 0.200 0.800
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0000 0.9401 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.9446 0.000 1.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.4690 0.8546 0.900 0.100
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.9754 0.2972 0.592 0.408
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.1633 0.9423 0.024 0.976
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.1633 0.9323 0.976 0.024
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0000 0.9446 0.000 1.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.9446 0.000 1.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 2 0.1633 0.9423 0.024 0.976
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.3431 0.9058 0.936 0.064
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 1 0.9795 0.3259 0.584 0.416
#> E789661A-C027-405D-9F76-E6D52CE3018B 1 0.9775 0.3369 0.588 0.412
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.1633 0.9323 0.976 0.024
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.9446 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.9401 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.9401 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.0000 0.9401 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.9401 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.1633 0.9423 0.024 0.976
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 1 0.9881 0.2668 0.564 0.436
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.9446 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9446 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9446 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.1633 0.9323 0.976 0.024
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.6801 0.7811 0.180 0.820
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9401 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9401 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9446 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9401 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9401 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9401 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.9401 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9401 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.1633 0.9423 0.024 0.976
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.1633 0.9423 0.024 0.976
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.1633 0.9323 0.976 0.024
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.1633 0.9323 0.976 0.024
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9401 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.9446 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.9401 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.1633 0.9268 0.976 0.024
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.1633 0.9423 0.024 0.976
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.9401 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.9401 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.8763 0.5966 0.296 0.704
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9401 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.1633 0.9323 0.976 0.024
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.1633 0.9323 0.976 0.024
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.9446 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9446 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.9401 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.9446 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.1633 0.9423 0.024 0.976
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.1633 0.9423 0.024 0.976
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9401 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9446 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.1633 0.9323 0.976 0.024
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9401 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.9661 0.3913 0.392 0.608
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9446 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.8016 0.6926 0.756 0.244
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9401 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.9286 0.4627 0.656 0.344
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.9401 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9401 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9446 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9446 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.1633 0.9323 0.976 0.024
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.1843 0.9401 0.028 0.972
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9401 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.1633 0.9423 0.024 0.976
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.1633 0.9423 0.024 0.976
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.9922 0.1710 0.552 0.448
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.1633 0.9423 0.024 0.976
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.1633 0.9423 0.024 0.976
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0376 0.9383 0.996 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9401 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.9401 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.1633 0.9323 0.976 0.024
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.6801 0.7571 0.180 0.820
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.2236 0.9349 0.036 0.964
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.1633 0.9423 0.024 0.976
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9401 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9446 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9446 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9401 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 1.0000 0.0100 0.500 0.500
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.1633 0.9423 0.024 0.976
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9401 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0938 0.9340 0.988 0.012
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.1633 0.9323 0.976 0.024
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.1633 0.9323 0.976 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.1633 0.9323 0.976 0.024
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9401 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.1633 0.9323 0.976 0.024
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9401 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9401 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.1633 0.9423 0.024 0.976
#> 1122039D-5785-4F70-9916-17C585453512 1 0.1633 0.9323 0.976 0.024
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4022 0.8758 0.920 0.080
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.1633 0.9423 0.024 0.976
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.2603 0.9211 0.956 0.044
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.9552 0.4280 0.624 0.376
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9446 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.9401 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.1633 0.9323 0.976 0.024
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.9401 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9401 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.1633 0.9423 0.024 0.976
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.3431 0.8929 0.936 0.064
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.9358 0.4353 0.352 0.648
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9401 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.8144 0.6771 0.748 0.252
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.9998 0.0147 0.508 0.492
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9401 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.1633 0.9423 0.024 0.976
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.1633 0.9423 0.024 0.976
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.9833 0.2340 0.424 0.576
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9401 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.9401 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9401 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9401 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.1633 0.9323 0.976 0.024
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9401 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9446 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.1633 0.9423 0.024 0.976
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9446 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9401 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1633 0.9323 0.976 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.9401 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9401 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.948 0.000 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.955 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.944 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.0000 0.955 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1643 0.917 0.044 0.956 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.944 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.2448 0.889 0.076 0.924 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.6274 0.159 0.544 0.000 0.456
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 0.944 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0000 0.944 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.948 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0592 0.936 0.012 0.000 0.988
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.948 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.8876 0.105 0.120 0.412 0.468
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.955 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0000 0.944 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0000 0.955 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.948 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.948 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.948 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.5915 0.770 0.128 0.792 0.080
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.948 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.955 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.948 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.955 1.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.948 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.944 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.955 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4178 0.776 0.828 0.000 0.172
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.0592 0.936 0.012 0.000 0.988
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#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0592 0.941 0.012 0.988 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.948 0.000 1.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.948 0.000 1.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.948 0.000 1.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.955 1.000 0.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.6140 0.317 0.000 0.404 0.596
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.955 1.000 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.955 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.948 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0000 0.944 0.000 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.955 1.000 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.955 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.955 1.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.955 1.000 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.944 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0000 0.944 0.000 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0000 0.955 1.000 0.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.955 1.000 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.955 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.948 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.955 1.000 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0000 0.944 0.000 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.944 0.000 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.955 1.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.3816 0.799 0.148 0.000 0.852
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.6587 0.428 0.016 0.632 0.352
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.955 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.5810 0.527 0.336 0.664 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.0000 0.955 1.000 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.948 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.948 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.955 1.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.948 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0000 0.944 0.000 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.944 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.955 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.948 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.955 1.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.955 1.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.0000 0.944 0.000 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.948 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.5760 0.544 0.328 0.672 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.955 1.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.944 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.5988 0.434 0.368 0.000 0.632
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.955 1.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.948 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.948 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.955 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.944 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.955 1.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.0000 0.944 0.000 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.944 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.0592 0.936 0.012 0.000 0.988
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0000 0.944 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.944 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0000 0.944 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.3340 0.834 0.120 0.000 0.880
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.5678 0.552 0.684 0.000 0.316
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1163 0.929 0.028 0.972 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.8399 0.486 0.136 0.256 0.608
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.0000 0.944 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0424 0.939 0.000 0.008 0.992
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.955 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.948 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.948 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.955 1.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0000 0.944 0.000 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.944 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.955 1.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0000 0.944 0.000 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.2066 0.903 0.060 0.940 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.955 1.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.955 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.955 1.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0237 0.946 0.004 0.996 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.955 1.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.955 1.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.944 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.955 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 3 0.6154 0.313 0.408 0.000 0.592
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.0000 0.944 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.948 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.948 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.1643 0.913 0.000 0.956 0.044
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.955 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0000 0.955 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.955 1.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1643 0.919 0.956 0.000 0.044
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.944 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.6448 0.437 0.636 0.012 0.352
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.948 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.955 1.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0237 0.946 0.004 0.996 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.944 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.4452 0.743 0.192 0.000 0.808
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.0000 0.944 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.944 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.948 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.2796 0.873 0.908 0.000 0.092
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.6267 0.178 0.452 0.000 0.548
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4605 0.730 0.796 0.000 0.204
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.955 1.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.955 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.955 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.6295 0.101 0.000 0.472 0.528
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.944 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.948 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3482 0.832 0.872 0.000 0.128
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.955 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.3482 0.823 0.128 0.000 0.872
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.955 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3726 0.6828 0.212 0.788 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0921 0.8665 0.028 0.000 0.972 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0336 0.7871 0.000 0.000 0.008 0.992
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4761 0.5522 0.000 0.628 0.000 0.372
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4500 0.5013 0.316 0.000 0.684 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4697 0.6510 0.000 0.696 0.008 0.296
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0592 0.7546 0.984 0.000 0.000 0.016
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0188 0.8657 0.004 0.000 0.996 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4522 0.5112 0.320 0.000 0.680 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0592 0.8686 0.016 0.984 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3074 0.7062 0.848 0.000 0.152 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0188 0.8744 0.000 0.996 0.000 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5698 0.3586 0.608 0.356 0.036 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.4888 0.2676 0.412 0.000 0.588 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0188 0.8744 0.000 0.996 0.000 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.4522 0.6252 0.000 0.680 0.000 0.320
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.6973 0.3273 0.000 0.556 0.300 0.144
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.4981 -0.1550 0.536 0.000 0.000 0.464
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.0188 0.7900 0.004 0.000 0.000 0.996
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4972 0.1126 0.456 0.000 0.544 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2214 0.7413 0.928 0.000 0.028 0.044
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0657 0.7557 0.984 0.000 0.012 0.004
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.7541 1.000 0.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.1118 0.8531 0.036 0.000 0.964 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.2973 0.7366 0.856 0.000 0.144 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4477 0.5234 0.312 0.000 0.688 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4989 0.3488 0.000 0.528 0.000 0.472
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.6776 0.5601 0.216 0.000 0.176 0.608
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.3311 0.7515 0.172 0.000 0.000 0.828
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0188 0.7879 0.000 0.004 0.000 0.996
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0921 0.7547 0.972 0.000 0.028 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.5432 0.6285 0.716 0.000 0.216 0.068
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.4679 0.2232 0.648 0.000 0.000 0.352
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1022 0.8666 0.032 0.000 0.968 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4877 0.3397 0.000 0.408 0.592 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.6068 -0.1767 0.508 0.000 0.044 0.448
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4679 0.4165 0.648 0.000 0.352 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5587 0.1102 0.600 0.000 0.028 0.372
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4713 0.4010 0.360 0.000 0.640 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.4564 0.4758 0.328 0.000 0.672 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.4585 0.6095 0.332 0.000 0.000 0.668
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.4164 0.5048 0.264 0.000 0.000 0.736
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4888 0.4841 0.000 0.588 0.000 0.412
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.1022 0.8666 0.032 0.000 0.968 0.000
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#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0921 0.8665 0.028 0.000 0.972 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4907 0.4702 0.000 0.580 0.000 0.420
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.3791 0.6966 0.200 0.796 0.004 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.3074 0.7062 0.848 0.000 0.152 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0707 0.7542 0.980 0.000 0.000 0.020
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.4948 -0.0897 0.560 0.000 0.000 0.440
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.4898 0.2173 0.000 0.584 0.416 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.2011 0.7439 0.920 0.000 0.080 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.4522 0.6220 0.320 0.000 0.000 0.680
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.1389 0.7445 0.952 0.000 0.000 0.048
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.2216 0.7241 0.908 0.000 0.000 0.092
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 4 0.4730 0.5658 0.364 0.000 0.000 0.636
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0336 0.8652 0.008 0.000 0.992 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0188 0.8657 0.004 0.000 0.996 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 4 0.4817 0.4011 0.388 0.000 0.000 0.612
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.4948 -0.0897 0.560 0.000 0.000 0.440
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0188 0.8745 0.000 0.996 0.004 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 4 0.3400 0.7475 0.180 0.000 0.000 0.820
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0592 0.8615 0.016 0.000 0.984 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.3123 0.7602 0.156 0.000 0.844 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 4 0.3400 0.7477 0.180 0.000 0.000 0.820
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.3219 0.7121 0.164 0.000 0.836 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.6416 0.5587 0.648 0.200 0.152 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.4522 0.6220 0.320 0.000 0.000 0.680
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.4877 0.4916 0.000 0.592 0.000 0.408
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.4866 0.2602 0.000 0.596 0.404 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.2281 0.7216 0.904 0.000 0.000 0.096
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0188 0.8745 0.000 0.996 0.004 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.1022 0.8666 0.032 0.000 0.968 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0188 0.8657 0.004 0.000 0.996 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.4907 0.4456 0.420 0.000 0.000 0.580
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4643 0.3317 0.656 0.000 0.000 0.344
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.2216 0.7986 0.092 0.000 0.908 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4888 0.4841 0.000 0.588 0.000 0.412
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.5708 0.0226 0.556 0.000 0.028 0.416
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.1389 0.8484 0.048 0.000 0.952 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.4925 0.2169 0.572 0.000 0.428 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.4040 0.6973 0.248 0.000 0.000 0.752
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0336 0.8652 0.008 0.000 0.992 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 4 0.3266 0.7533 0.168 0.000 0.000 0.832
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4406 0.5084 0.700 0.000 0.300 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0188 0.8657 0.004 0.000 0.996 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.3219 0.6955 0.836 0.000 0.164 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.1118 0.8660 0.036 0.000 0.964 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0188 0.8657 0.004 0.000 0.996 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.2345 0.7911 0.100 0.000 0.900 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0336 0.7560 0.992 0.000 0.008 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0921 0.7523 0.972 0.000 0.000 0.028
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.4761 0.5537 0.000 0.628 0.000 0.372
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3626 0.7086 0.000 0.004 0.812 0.184
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4746 0.3928 0.632 0.000 0.368 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0921 0.8665 0.028 0.000 0.972 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.1940 0.7346 0.924 0.000 0.000 0.076
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0469 0.8706 0.012 0.988 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0188 0.8745 0.000 0.996 0.004 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.4454 0.6363 0.308 0.000 0.000 0.692
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.4134 0.6119 0.740 0.000 0.260 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.1022 0.8666 0.032 0.000 0.968 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.4564 0.6145 0.328 0.000 0.000 0.672
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0921 0.8548 0.028 0.000 0.972 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.7599 0.2655 0.200 0.424 0.000 0.376
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.4564 0.6145 0.328 0.000 0.000 0.672
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.5404 0.5986 0.028 0.644 0.000 0.328
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.4564 0.6145 0.328 0.000 0.000 0.672
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.4543 0.6185 0.324 0.000 0.000 0.676
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0336 0.8652 0.008 0.000 0.992 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.3219 0.6988 0.836 0.000 0.164 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.4855 0.2966 0.600 0.000 0.400 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.3801 0.5690 0.000 0.220 0.000 0.780
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.4820 0.6487 0.012 0.692 0.000 0.296
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.4996 0.1068 0.000 0.484 0.516 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.5364 0.6120 0.320 0.000 0.028 0.652
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.5423 0.5924 0.332 0.000 0.028 0.640
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0921 0.7509 0.972 0.000 0.028 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0921 0.8665 0.028 0.000 0.972 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.8058 0.3200 0.468 0.016 0.288 0.228
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3873 0.7234 0.000 0.772 0.000 0.228
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.3356 0.7498 0.176 0.000 0.000 0.824
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4585 0.6101 0.000 0.668 0.000 0.332
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.3688 0.7003 0.208 0.000 0.792 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.1211 0.7532 0.960 0.000 0.040 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3356 0.6860 0.824 0.000 0.176 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4500 0.5013 0.316 0.000 0.684 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4250 0.6755 0.000 0.724 0.000 0.276
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0921 0.7509 0.972 0.000 0.028 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.1118 0.7511 0.964 0.000 0.036 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.5756 0.5215 0.372 0.000 0.036 0.592
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1716 0.7392 0.936 0.000 0.000 0.064
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.7900 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.3942 0.5496 0.764 0.000 0.000 0.236
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.3764 0.6810 0.000 0.216 0.784 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0921 0.8665 0.028 0.000 0.972 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.8756 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.7541 1.000 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 4 0.0804 0.7835 0.008 0.000 0.012 0.980
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.7231 0.2272 0.192 0.000 0.540 0.268
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2408 0.7157 0.896 0.000 0.000 0.104
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4114 0.343929 0.376 0.624 0.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.761441 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 5 0.4294 -0.087458 0.000 0.000 0.468 0.000 0.532
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0000 0.761441 0.000 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.6710 0.359717 0.000 0.424 0.000 0.304 0.272
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.5504 0.114546 0.224 0.000 0.644 0.000 0.132
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 5 0.6518 -0.353327 0.000 0.376 0.008 0.152 0.464
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.4256 -0.383235 0.436 0.000 0.564 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 5 0.4443 -0.002555 0.004 0.000 0.472 0.000 0.524
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4599 0.203003 0.384 0.000 0.600 0.000 0.016
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.4114 0.343929 0.376 0.624 0.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.4201 -0.355891 0.408 0.000 0.592 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1121 0.639657 0.000 0.956 0.000 0.044 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.6613 0.224442 0.288 0.560 0.104 0.000 0.048
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0579 0.762593 0.008 0.000 0.008 0.984 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5274 0.355340 0.132 0.000 0.676 0.000 0.192
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.761441 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0963 0.642593 0.000 0.964 0.000 0.036 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.3715 0.519163 0.000 0.736 0.000 0.260 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.652604 0.000 1.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.5713 0.232750 0.000 0.600 0.016 0.068 0.316
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1270 0.648016 0.000 0.948 0.000 0.000 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.5028 0.543315 0.400 0.000 0.036 0.564 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0162 0.652382 0.000 0.996 0.000 0.000 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.3209 0.747799 0.180 0.000 0.008 0.812 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.1965 0.590478 0.000 0.904 0.000 0.000 0.096
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5684 -0.206465 0.340 0.000 0.564 0.000 0.096
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6263 0.482330 0.456 0.000 0.448 0.056 0.040
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4182 0.539087 0.600 0.000 0.400 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4210 0.531314 0.588 0.000 0.412 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4747 0.002687 0.016 0.000 0.496 0.000 0.488
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.652604 0.000 1.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.761441 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4769 0.468045 0.688 0.000 0.256 0.000 0.056
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4752 0.346844 0.092 0.000 0.724 0.000 0.184
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.0613 0.762008 0.004 0.000 0.008 0.984 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 5 0.8088 -0.337470 0.060 0.344 0.032 0.156 0.408
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.6443 0.546174 0.064 0.000 0.136 0.632 0.168
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.3551 0.736726 0.220 0.000 0.008 0.772 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.761441 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.4510 -0.375204 0.432 0.000 0.560 0.000 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4958 0.516460 0.568 0.000 0.400 0.000 0.032
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.4227 0.528916 0.000 0.580 0.000 0.000 0.420
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3774 0.093276 0.704 0.000 0.000 0.296 0.000
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cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.3765 0.35081 0.000 0.000 0.000 0.000 0.596 0.404
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1584 0.80379 0.000 0.008 0.928 0.000 0.000 0.064
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.6035 0.17089 0.000 0.248 0.000 0.376 0.376 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.5679 0.50396 0.612 0.028 0.172 0.000 0.000 0.188
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3636 0.54825 0.676 0.000 0.004 0.000 0.000 0.320
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0363 0.80069 0.000 0.000 0.988 0.000 0.000 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 6 0.2805 0.36580 0.000 0.000 0.184 0.000 0.004 0.812
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0508 0.82322 0.000 0.004 0.000 0.000 0.984 0.012
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3650 0.58915 0.708 0.000 0.012 0.000 0.000 0.280
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.5453 0.40920 0.040 0.012 0.040 0.000 0.604 0.304
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1464 0.61802 0.016 0.004 0.000 0.944 0.000 0.036
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.6088 0.11486 0.296 0.000 0.392 0.000 0.000 0.312
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.4403 0.41257 0.000 0.028 0.000 0.408 0.564 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 5 0.6370 0.18227 0.000 0.016 0.328 0.244 0.412 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.3428 0.52842 0.000 0.304 0.000 0.000 0.696 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.5902 0.32713 0.304 0.000 0.000 0.184 0.008 0.504
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 5 0.0713 0.82396 0.000 0.028 0.000 0.000 0.972 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.4695 0.54763 0.232 0.000 0.000 0.684 0.012 0.072
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.0520 0.82528 0.000 0.008 0.008 0.000 0.984 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.5157 0.57801 0.692 0.056 0.084 0.000 0.000 0.168
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.5166 0.11931 0.528 0.000 0.060 0.000 0.012 0.400
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0458 0.64237 0.984 0.000 0.000 0.000 0.000 0.016
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1531 0.65115 0.928 0.000 0.004 0.000 0.000 0.068
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2697 0.68228 0.000 0.000 0.812 0.000 0.000 0.188
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 6 0.4695 0.27056 0.232 0.000 0.072 0.000 0.012 0.684
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.6073 0.12750 0.268 0.000 0.380 0.000 0.000 0.352
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.1511 0.61760 0.012 0.012 0.000 0.944 0.000 0.032
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.3534 0.76102 0.076 0.800 0.000 0.124 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.6859 0.09506 0.024 0.000 0.328 0.368 0.012 0.268
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.5483 0.50292 0.280 0.000 0.000 0.584 0.012 0.124
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3817 0.43021 0.568 0.000 0.000 0.000 0.000 0.432
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1700 0.62276 0.928 0.000 0.048 0.000 0.000 0.024
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0547 0.86508 0.000 0.980 0.000 0.000 0.020 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.5654 0.36949 0.304 0.000 0.000 0.160 0.004 0.532
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.2114 0.58260 0.012 0.076 0.000 0.904 0.000 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.2454 0.78549 0.000 0.000 0.840 0.000 0.000 0.160
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4671 0.19491 0.000 0.000 0.532 0.044 0.424 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 6 0.6302 0.41830 0.104 0.000 0.184 0.116 0.004 0.592
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 6 0.6036 0.12294 0.300 0.076 0.064 0.000 0.004 0.556
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.6887 0.22364 0.180 0.000 0.080 0.212 0.012 0.516
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.4582 0.60206 0.732 0.032 0.068 0.000 0.000 0.168
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 5 0.4853 0.54160 0.000 0.004 0.000 0.292 0.628 0.076
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5693 0.50235 0.616 0.032 0.176 0.000 0.000 0.176
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.6061 0.38538 0.384 0.000 0.000 0.432 0.012 0.172
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.5898 0.10549 0.204 0.000 0.000 0.380 0.000 0.416
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0865 0.86090 0.000 0.964 0.000 0.000 0.036 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.3695 0.51663 0.000 0.624 0.000 0.376 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.5296 0.55185 0.184 0.000 0.600 0.000 0.000 0.216
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 5 0.2932 0.71997 0.000 0.016 0.000 0.164 0.820 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0632 0.64454 0.976 0.000 0.000 0.000 0.000 0.024
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2482 0.79488 0.000 0.848 0.000 0.148 0.004 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 4 0.5839 0.44493 0.360 0.000 0.000 0.488 0.012 0.140
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0632 0.64454 0.976 0.000 0.000 0.000 0.000 0.024
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.4120 0.01452 0.004 0.000 0.524 0.000 0.004 0.468
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3866 0.45235 0.000 0.000 0.516 0.000 0.000 0.484
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.3578 0.46862 0.000 0.000 0.000 0.000 0.660 0.340
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3937 -0.16018 0.572 0.000 0.000 0.000 0.004 0.424
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0622 0.63307 0.980 0.000 0.008 0.000 0.000 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 4 0.6898 0.41604 0.284 0.000 0.056 0.468 0.012 0.180
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 5 0.3314 0.65129 0.000 0.004 0.000 0.256 0.740 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.4135 0.28539 0.008 0.584 0.000 0.000 0.004 0.404
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0713 0.86343 0.000 0.972 0.000 0.000 0.028 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 5 0.4338 -0.02068 0.000 0.000 0.484 0.020 0.496 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.3875 0.75760 0.020 0.036 0.776 0.000 0.000 0.168
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1588 0.80322 0.000 0.004 0.924 0.000 0.000 0.072
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.2883 0.66182 0.000 0.000 0.000 0.000 0.788 0.212
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0260 0.80144 0.008 0.000 0.992 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.3210 0.77759 0.000 0.036 0.812 0.000 0.000 0.152
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.2092 0.57218 0.876 0.124 0.000 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.0520 0.82528 0.000 0.008 0.008 0.000 0.984 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0547 0.62220 0.980 0.000 0.000 0.000 0.000 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0777 0.80552 0.000 0.004 0.972 0.000 0.000 0.024
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 4 0.5015 0.52212 0.284 0.000 0.000 0.628 0.012 0.076
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 4 0.5830 0.43545 0.372 0.000 0.000 0.480 0.012 0.136
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1387 0.80430 0.000 0.000 0.932 0.000 0.000 0.068
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 4 0.7165 0.32218 0.316 0.000 0.060 0.396 0.012 0.216
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 6 0.7262 0.05025 0.204 0.000 0.080 0.284 0.012 0.420
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.5720 0.49591 0.612 0.032 0.184 0.000 0.000 0.172
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0777 0.61948 0.972 0.004 0.000 0.000 0.000 0.024
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.3330 0.49663 0.716 0.000 0.000 0.000 0.000 0.284
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.1663 0.77252 0.000 0.000 0.000 0.000 0.912 0.088
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 5 0.5834 0.33541 0.000 0.204 0.000 0.328 0.468 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1204 0.85307 0.000 0.944 0.000 0.000 0.056 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 6 0.7260 -0.03385 0.200 0.000 0.076 0.312 0.012 0.400
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 4 0.7127 0.32258 0.320 0.000 0.056 0.396 0.012 0.216
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 5 0.5025 0.44720 0.000 0.108 0.284 0.000 0.608 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 4 0.7040 0.35637 0.324 0.000 0.056 0.416 0.012 0.192
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.4670 0.12249 0.000 0.000 0.548 0.036 0.004 0.412
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.2980 0.50640 0.000 0.000 0.192 0.800 0.000 0.008
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.5209 0.50706 0.612 0.000 0.168 0.000 0.000 0.220
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 5 0.2996 0.63980 0.000 0.228 0.000 0.000 0.772 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 6 0.5869 0.33384 0.284 0.000 0.000 0.208 0.004 0.504
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 4 0.6358 -0.04714 0.000 0.300 0.000 0.400 0.288 0.012
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.2631 0.77075 0.000 0.820 0.000 0.180 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 6 0.5056 -0.04407 0.392 0.024 0.036 0.000 0.000 0.548
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 4 0.5519 -0.02775 0.000 0.144 0.000 0.512 0.344 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 6 0.3296 0.36941 0.020 0.000 0.180 0.000 0.004 0.796
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1141 0.85498 0.000 0.948 0.000 0.000 0.052 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0260 0.80156 0.000 0.000 0.992 0.000 0.000 0.008
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 6 0.4442 0.37123 0.440 0.000 0.000 0.020 0.004 0.536
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.1409 0.78514 0.008 0.000 0.948 0.000 0.012 0.032
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 4 0.6068 0.40032 0.368 0.000 0.000 0.444 0.012 0.176
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0937 0.85880 0.000 0.960 0.000 0.040 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 6 0.2848 0.42120 0.008 0.000 0.004 0.000 0.160 0.828
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 5 0.0363 0.82116 0.000 0.000 0.000 0.000 0.988 0.012
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.2730 0.78830 0.012 0.836 0.000 0.152 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.4457 0.59399 0.704 0.012 0.056 0.000 0.000 0.228
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 4 0.6991 0.37692 0.316 0.000 0.056 0.432 0.012 0.184
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 4 0.1814 0.53758 0.000 0.000 0.000 0.900 0.100 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.3742 0.54530 0.648 0.000 0.004 0.000 0.000 0.348
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0458 0.79957 0.000 0.000 0.984 0.000 0.000 0.016
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 1 0.4455 0.58158 0.684 0.000 0.076 0.000 0.000 0.240
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.4805 0.19818 0.696 0.000 0.000 0.116 0.012 0.176
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.2491 0.78716 0.000 0.000 0.836 0.000 0.000 0.164
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.4076 0.14062 0.000 0.540 0.452 0.000 0.008 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 4 0.5719 0.46289 0.344 0.000 0.000 0.516 0.012 0.128
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0260 0.80156 0.000 0.000 0.992 0.000 0.000 0.008
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#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.5750 0.46293 0.344 0.000 0.000 0.512 0.012 0.132
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1007 0.85835 0.000 0.956 0.000 0.000 0.044 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0632 0.79755 0.000 0.000 0.976 0.000 0.000 0.024
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 4 0.5818 0.44537 0.364 0.000 0.000 0.488 0.012 0.136
#> EE40EE80-4520-4643-B906-48246BA616A7 6 0.3665 0.18837 0.252 0.000 0.020 0.000 0.000 0.728
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0632 0.79755 0.000 0.000 0.976 0.000 0.000 0.024
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 6 0.3190 0.25276 0.220 0.000 0.008 0.000 0.000 0.772
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.3309 0.72496 0.000 0.000 0.720 0.000 0.000 0.280
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0260 0.80156 0.000 0.000 0.992 0.000 0.000 0.008
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0520 0.80034 0.008 0.000 0.984 0.000 0.000 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.2933 0.63135 0.796 0.000 0.004 0.000 0.000 0.200
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.2527 0.58144 0.832 0.000 0.000 0.000 0.000 0.168
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0937 0.85880 0.000 0.960 0.000 0.040 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.1349 0.78270 0.000 0.000 0.940 0.056 0.000 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 6 0.3010 0.41830 0.020 0.000 0.148 0.000 0.004 0.828
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.3307 0.77682 0.000 0.044 0.808 0.000 0.000 0.148
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0547 0.62220 0.980 0.000 0.000 0.000 0.000 0.020
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0363 0.82116 0.000 0.000 0.000 0.000 0.988 0.012
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.86472 0.000 1.000 0.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.5812 0.42915 0.380 0.000 0.000 0.476 0.012 0.132
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.3979 0.59457 0.708 0.000 0.036 0.000 0.000 0.256
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2697 0.77347 0.000 0.000 0.812 0.000 0.000 0.188
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.6061 0.38538 0.384 0.000 0.000 0.432 0.012 0.172
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0717 0.79835 0.000 0.000 0.976 0.000 0.008 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 6 0.6156 0.12727 0.000 0.252 0.000 0.344 0.004 0.400
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0260 0.62015 0.000 0.000 0.000 0.992 0.000 0.008
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.5840 0.42672 0.380 0.000 0.000 0.472 0.012 0.136
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.6332 -0.07562 0.000 0.012 0.000 0.412 0.272 0.304
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.6037 0.39524 0.380 0.000 0.000 0.440 0.012 0.168
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.5864 0.39621 0.408 0.000 0.000 0.444 0.012 0.136
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3151 0.71288 0.000 0.000 0.748 0.000 0.000 0.252
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 6 0.3409 0.43375 0.184 0.000 0.024 0.000 0.004 0.788
#> E678189F-D5CF-4C45-8E53-58ECB8448058 6 0.3344 0.38207 0.044 0.000 0.152 0.000 0.000 0.804
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.2730 0.44869 0.000 0.000 0.000 0.808 0.192 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.1686 0.79180 0.000 0.000 0.000 0.064 0.924 0.012
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0458 0.85658 0.000 0.984 0.016 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.7308 0.26984 0.232 0.000 0.076 0.404 0.012 0.276
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.6058 0.39044 0.380 0.000 0.000 0.436 0.012 0.172
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.4607 0.28875 0.356 0.000 0.028 0.000 0.012 0.604
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3210 0.77759 0.000 0.036 0.812 0.000 0.000 0.152
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.2697 0.72796 0.188 0.812 0.000 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1387 0.84731 0.000 0.932 0.000 0.068 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.5731 0.47585 0.324 0.000 0.000 0.528 0.012 0.136
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.3778 0.59006 0.000 0.016 0.000 0.288 0.696 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.5156 0.51574 0.600 0.000 0.128 0.000 0.000 0.272
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3052 0.62593 0.780 0.000 0.004 0.000 0.000 0.216
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 6 0.2728 0.42234 0.032 0.000 0.004 0.000 0.100 0.864
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5721 0.49789 0.612 0.032 0.180 0.000 0.000 0.176
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 5 0.5933 0.28332 0.000 0.252 0.000 0.288 0.460 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 6 0.4189 0.25933 0.376 0.000 0.020 0.000 0.000 0.604
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 6 0.3172 0.50084 0.092 0.000 0.076 0.000 0.000 0.832
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.7075 0.13893 0.176 0.000 0.084 0.252 0.012 0.476
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0547 0.62220 0.980 0.000 0.000 0.000 0.000 0.020
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.62033 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.63513 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.2871 0.70169 0.000 0.000 0.804 0.000 0.192 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3054 0.78401 0.000 0.036 0.828 0.000 0.000 0.136
#> A0C429D9-0638-4873-BFB4-00056AB4719F 5 0.0458 0.82911 0.000 0.016 0.000 0.000 0.984 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.1204 0.64802 0.944 0.000 0.000 0.000 0.000 0.056
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.6092 0.03535 0.092 0.484 0.000 0.384 0.012 0.028
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5161 0.40648 0.000 0.000 0.640 0.112 0.012 0.236
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0547 0.62220 0.980 0.000 0.000 0.000 0.000 0.020
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.456 0.784 0.894 0.4754 0.526 0.526
#> 3 3 0.442 0.706 0.814 0.3016 0.843 0.710
#> 4 4 0.505 0.581 0.789 0.1539 0.759 0.474
#> 5 5 0.634 0.582 0.791 0.0707 0.897 0.670
#> 6 6 0.609 0.440 0.694 0.0429 0.855 0.532
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.7219 0.6800 0.200 0.800
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.7219 0.7498 0.800 0.200
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.5842 0.8170 0.140 0.860
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.9608 0.5597 0.616 0.384
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.9710 0.5296 0.600 0.400
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.8615 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.2423 0.8761 0.040 0.960
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.8615 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.6247 0.8025 0.156 0.844
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.6438 0.7728 0.836 0.164
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.9661 0.5453 0.608 0.392
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.8615 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.8977 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.7299 0.7456 0.796 0.204
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6623 0.7692 0.828 0.172
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5946 0.7882 0.856 0.144
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.7139 0.7522 0.804 0.196
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.7453 0.6589 0.212 0.788
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.9850 0.4681 0.572 0.428
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.8977 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.8977 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.8977 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8615 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.8977 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1633 0.8562 0.976 0.024
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.8977 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0376 0.8609 0.996 0.004
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.8615 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.8615 1.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.8615 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6887 0.7537 0.816 0.184
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.8977 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.9608 0.5597 0.616 0.384
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.8615 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.8615 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.6973 0.7585 0.812 0.188
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.2423 0.8522 0.960 0.040
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0672 0.8601 0.992 0.008
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.1184 0.8581 0.984 0.016
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.9608 0.5597 0.616 0.384
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.8615 1.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1843 0.8553 0.972 0.028
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.8977 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8615 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.6712 0.7658 0.824 0.176
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.6247 0.7800 0.844 0.156
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.8977 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.4298 0.8313 0.912 0.088
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.8661 0.5459 0.712 0.288
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.9988 -0.1972 0.480 0.520
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.8615 1.000 0.000
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#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.9608 0.5597 0.616 0.384
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.8615 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.8615 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0938 0.8593 0.988 0.012
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0376 0.8608 0.996 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.8977 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.8977 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.9608 0.5597 0.616 0.384
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.6887 0.7541 0.816 0.184
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.8267 0.6899 0.740 0.260
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.8615 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.9661 0.3920 0.608 0.392
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.8615 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.7883 0.7012 0.764 0.236
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.3733 0.8644 0.072 0.928
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0376 0.8608 0.996 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.8615 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.8615 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.7376 0.6660 0.208 0.792
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.0000 0.8977 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.0000 0.8615 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.5842 0.8170 0.140 0.860
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.8615 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.8977 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.8977 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.8615 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.8615 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.7139 0.7434 0.804 0.196
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.8615 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1633 0.8568 0.976 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.9635 0.5527 0.612 0.388
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.6712 0.7642 0.824 0.176
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.7139 0.7522 0.804 0.196
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.8615 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.8763 0.6730 0.704 0.296
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.8615 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.8615 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.7139 0.7434 0.804 0.196
#> 1122039D-5785-4F70-9916-17C585453512 1 0.9393 0.6005 0.644 0.356
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.8615 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.8615 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.9608 0.5597 0.616 0.384
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.9608 0.5597 0.616 0.384
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.8977 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0938 0.8593 0.988 0.012
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.9881 0.4447 0.564 0.436
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.8615 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.8615 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.6623 0.7875 0.172 0.828
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.5408 0.8296 0.124 0.876
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.7139 0.6871 0.196 0.804
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0672 0.8601 0.992 0.008
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.9608 0.5597 0.616 0.384
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.8615 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.8615 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.8615 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0938 0.8574 0.988 0.012
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.8977 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.8615 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.8615 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.8615 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.8615 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.9608 0.5597 0.616 0.384
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.8615 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.8977 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.5737 0.8205 0.136 0.864
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.8977 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.8615 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.9491 0.5812 0.632 0.368
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4298 0.8281 0.912 0.088
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.8615 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5216 0.5957 0.260 0.740 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.4399 0.8267 0.000 0.188 0.812
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.5558 0.7498 0.152 0.800 0.048
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.9206 0.4885 0.524 0.288 0.188
#> BE685EF3-953B-483C-A99C-75FBF81D6615 3 0.8717 0.5402 0.220 0.188 0.592
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.7435 1.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.1411 0.8133 0.036 0.964 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3038 0.7651 0.896 0.000 0.104
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.5442 0.7570 0.132 0.812 0.056
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.2173 0.7381 0.944 0.008 0.048
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.6865 0.5413 0.596 0.384 0.020
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.7435 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0592 0.8294 0.000 0.988 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.6808 0.7565 0.732 0.084 0.184
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.3028 0.7716 0.032 0.048 0.920
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0424 0.7423 0.992 0.008 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.4399 0.8267 0.000 0.188 0.812
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.5268 0.5845 0.212 0.776 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 3 0.4399 0.8267 0.000 0.188 0.812
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.8373 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.8478 0.5497 0.204 0.180 0.616
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.6252 -0.0696 0.000 0.556 0.444
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.5591 0.7259 0.696 0.000 0.304
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.8373 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.1753 0.7523 0.048 0.000 0.952
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.8373 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0661 0.7458 0.988 0.004 0.008
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.6297 0.7215 0.640 0.008 0.352
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3619 0.7696 0.864 0.000 0.136
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3686 0.7632 0.860 0.000 0.140
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6677 0.6934 0.740 0.180 0.080
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.8373 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.4399 0.8267 0.000 0.188 0.812
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.1964 0.7431 0.944 0.000 0.056
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1753 0.7397 0.952 0.000 0.048
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.8824 0.5477 0.572 0.168 0.260
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.6284 0.7254 0.680 0.016 0.304
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.7826 0.7237 0.612 0.076 0.312
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.1753 0.7521 0.048 0.000 0.952
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4399 0.8267 0.000 0.188 0.812
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1964 0.7431 0.944 0.000 0.056
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.7412 0.7420 0.700 0.124 0.176
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.8373 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 3 0.2711 0.7213 0.088 0.000 0.912
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.4629 0.8254 0.004 0.188 0.808
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0592 0.7412 0.988 0.012 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.3116 0.7958 0.108 0.892 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.8605 0.6828 0.604 0.208 0.188
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.5016 0.4682 0.760 0.240 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.9710 0.1208 0.408 0.220 0.372
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.5650 0.7389 0.688 0.000 0.312
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.7435 1.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.4399 0.8267 0.000 0.188 0.812
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0000 0.7435 1.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.5591 0.7259 0.696 0.000 0.304
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.6008 0.6729 0.628 0.000 0.372
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.8373 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.8688 0.5657 0.596 0.196 0.208
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0424 0.7423 0.992 0.008 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.8681 0.5619 0.596 0.188 0.216
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3551 0.7637 0.868 0.000 0.132
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.8373 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.8137 0.6837 0.640 0.220 0.140
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.5291 0.7431 0.732 0.000 0.268
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 2 0.9306 -0.0253 0.336 0.488 0.176
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.2173 0.7381 0.944 0.008 0.048
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.8373 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.5497 0.7323 0.708 0.000 0.292
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3686 0.7632 0.860 0.000 0.140
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.6111 0.6895 0.604 0.000 0.396
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.4555 0.8168 0.000 0.200 0.800
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.7858 0.4958 0.572 0.364 0.064
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.8373 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.8373 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.6286 0.4626 0.464 0.536 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.4399 0.8267 0.000 0.188 0.812
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.5678 0.6480 0.316 0.684 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.6314 0.1045 0.392 0.604 0.004
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.5371 0.7000 0.048 0.812 0.140
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.3340 0.7101 0.880 0.120 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.7500 0.7238 0.696 0.164 0.140
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.8373 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.5591 0.7259 0.696 0.000 0.304
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.5371 0.7562 0.140 0.812 0.048
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.1753 0.7542 0.048 0.000 0.952
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.8373 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.6111 0.6895 0.604 0.000 0.396
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.6523 0.6925 0.228 0.724 0.048
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.7782 0.7423 0.652 0.100 0.248
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.8373 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4399 0.7629 0.812 0.000 0.188
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.2625 0.6888 0.916 0.084 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.5591 0.7259 0.696 0.000 0.304
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0424 0.8320 0.000 0.992 0.008
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.4654 0.7619 0.792 0.000 0.208
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.6168 0.5124 0.588 0.412 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.8373 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.8373 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.4399 0.8267 0.000 0.188 0.812
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.8373 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.5650 0.7389 0.688 0.000 0.312
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.5291 0.7547 0.732 0.000 0.268
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.1964 0.8129 0.056 0.944 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.8373 0.000 1.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.4887 0.7555 0.772 0.000 0.228
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.8561 0.2172 0.484 0.420 0.096
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#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.7552 0.7210 0.692 0.168 0.140
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.8624 0.5773 0.596 0.240 0.164
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.1964 0.7954 0.000 0.056 0.944
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.4291 0.8269 0.000 0.180 0.820
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.5926 0.7059 0.644 0.000 0.356
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 3 0.4399 0.8267 0.000 0.188 0.812
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.6111 0.6895 0.604 0.000 0.396
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.5216 0.7460 0.740 0.000 0.260
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.2173 0.7381 0.944 0.008 0.048
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4399 0.8267 0.000 0.188 0.812
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.3551 0.7661 0.868 0.000 0.132
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.1753 0.7397 0.952 0.000 0.048
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.4399 0.8267 0.000 0.188 0.812
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.6345 0.5272 0.596 0.400 0.004
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.8373 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.7388 0.7074 0.600 0.044 0.356
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.2066 0.7972 0.000 0.060 0.940
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.5621 0.7263 0.692 0.000 0.308
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.5254 0.7562 0.736 0.000 0.264
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.5650 0.6513 0.312 0.688 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.5981 0.6825 0.080 0.788 0.132
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4504 0.6198 0.196 0.804 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.6111 0.6895 0.604 0.000 0.396
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.8685 0.5640 0.596 0.192 0.212
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.1753 0.7397 0.952 0.000 0.048
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3482 0.7641 0.872 0.000 0.128
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1753 0.7397 0.952 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0000 0.7435 1.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4235 0.6201 0.000 0.824 0.176
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.5058 0.7609 0.756 0.000 0.244
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4399 0.7629 0.812 0.000 0.188
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.7388 0.7462 0.692 0.100 0.208
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4842 0.7548 0.776 0.000 0.224
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.4399 0.8267 0.000 0.188 0.812
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.5591 0.7259 0.696 0.000 0.304
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.8373 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.6481 0.6958 0.224 0.728 0.048
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.8373 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3551 0.7637 0.868 0.000 0.132
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6140 0.5234 0.596 0.404 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.8681 0.6771 0.596 0.216 0.188
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5591 0.7259 0.696 0.000 0.304
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5310 0.41947 0.012 0.576 0.412 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.4277 0.60391 0.000 0.720 0.280 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5311 0.30700 0.392 0.004 0.008 0.596
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.6616 0.54016 0.220 0.156 0.000 0.624
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4830 0.56649 0.392 0.000 0.608 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.3052 0.73872 0.136 0.860 0.004 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0921 0.71650 0.972 0.000 0.028 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.5198 0.62493 0.040 0.708 0.252 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1389 0.56554 0.048 0.000 0.952 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.6969 0.42298 0.192 0.584 0.224 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4977 -0.34362 0.540 0.000 0.460 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1302 0.79417 0.000 0.956 0.000 0.044
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5109 0.58411 0.744 0.060 0.196 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1389 0.77598 0.048 0.000 0.000 0.952
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.4222 0.57928 0.272 0.000 0.728 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.6065 0.56520 0.216 0.688 0.008 0.088
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.4746 0.67303 0.000 0.056 0.168 0.776
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6621 0.42063 0.000 0.140 0.244 0.616
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.4679 0.40830 0.000 0.648 0.000 0.352
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.4267 0.60650 0.788 0.000 0.188 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.4103 0.59466 0.256 0.000 0.000 0.744
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.1302 0.79296 0.000 0.956 0.044 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2611 0.71374 0.896 0.000 0.096 0.008
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5290 0.19968 0.404 0.000 0.584 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3486 0.60474 0.812 0.000 0.188 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6353 0.44591 0.652 0.140 0.208 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4643 0.34799 0.656 0.000 0.344 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.4605 0.52996 0.336 0.000 0.664 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.4916 0.22828 0.424 0.000 0.000 0.576
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.2949 0.69285 0.888 0.088 0.000 0.024
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.2773 0.70705 0.880 0.004 0.116 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.4981 0.19685 0.464 0.000 0.000 0.536
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4193 0.51869 0.732 0.000 0.268 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0188 0.72871 0.996 0.000 0.004 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.6994 0.33049 0.560 0.000 0.288 0.152
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.3099 0.74136 0.020 0.104 0.000 0.876
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3837 0.59791 0.224 0.000 0.776 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.2973 0.72959 0.000 0.856 0.144 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3758 0.68982 0.848 0.048 0.104 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.4194 0.49492 0.228 0.008 0.764 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 4 0.9459 0.29400 0.236 0.284 0.112 0.368
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.4948 -0.28484 0.560 0.000 0.440 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.3356 0.69076 0.000 0.176 0.000 0.824
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0469 0.72931 0.988 0.000 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.6162 0.55442 0.676 0.000 0.168 0.156
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.7894 -0.03708 0.372 0.332 0.000 0.296
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 4 0.7060 0.18044 0.400 0.124 0.000 0.476
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.4356 0.24595 0.708 0.000 0.292 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1211 0.79328 0.040 0.960 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3751 0.57330 0.800 0.196 0.000 0.004
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0895 0.72695 0.976 0.000 0.004 0.020
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.7900 -0.13157 0.344 0.296 0.360 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3266 0.58595 0.168 0.000 0.832 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.4331 0.58914 0.000 0.712 0.288 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.5198 0.49766 0.688 0.008 0.288 0.016
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.72730 1.000 0.000 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.3649 0.66285 0.000 0.204 0.000 0.796
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 3 0.7734 0.02541 0.160 0.372 0.456 0.012
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.1722 0.79136 0.008 0.944 0.048 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.6769 0.58457 0.172 0.220 0.608 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.6495 0.50692 0.108 0.284 0.608 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.6769 0.45907 0.172 0.608 0.220 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.5619 0.55552 0.268 0.676 0.056 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.5805 0.55925 0.388 0.036 0.576 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0188 0.72728 0.996 0.000 0.000 0.004
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0657 0.80324 0.012 0.984 0.004 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0817 0.72793 0.976 0.000 0.000 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.4220 0.64184 0.004 0.748 0.248 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 4 0.0707 0.78657 0.020 0.000 0.000 0.980
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.2647 0.69744 0.880 0.000 0.000 0.120
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4564 0.42449 0.000 0.328 0.672 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0707 0.72775 0.980 0.000 0.000 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.1211 0.79463 0.000 0.960 0.000 0.040
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.1389 0.72810 0.952 0.000 0.048 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.6324 0.46816 0.076 0.584 0.340 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2473 0.77741 0.012 0.908 0.000 0.080
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.3266 0.69845 0.000 0.832 0.168 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.2149 0.71814 0.912 0.000 0.088 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.1940 0.77459 0.076 0.924 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.1389 0.79173 0.000 0.952 0.048 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0336 0.72966 0.992 0.000 0.008 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.7120 -0.14919 0.136 0.368 0.496 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.1004 0.77926 0.004 0.024 0.000 0.972
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 4 0.6136 0.57665 0.080 0.000 0.288 0.632
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.7154 0.03048 0.432 0.436 0.000 0.132
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.6228 0.29880 0.364 0.572 0.000 0.064
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.3569 0.57630 0.196 0.000 0.804 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 4 0.3796 0.73296 0.000 0.096 0.056 0.848
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.3074 0.56203 0.152 0.000 0.848 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 2 0.5256 0.61209 0.040 0.700 0.260 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.4883 0.49885 0.696 0.000 0.288 0.016
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.3099 0.70657 0.876 0.020 0.104 0.000
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#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.5698 0.41227 0.036 0.356 0.608 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0592 0.72709 0.984 0.000 0.000 0.016
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.6769 0.42228 0.000 0.608 0.172 0.220
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.80436 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1022 0.72979 0.968 0.000 0.000 0.032
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.4948 0.53598 0.440 0.000 0.560 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.4605 0.52996 0.336 0.000 0.664 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2611 0.71374 0.896 0.000 0.096 0.008
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1356 0.72411 0.960 0.032 0.008 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.8062 0.41534 0.072 0.536 0.288 0.104
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.2089 0.72735 0.932 0.000 0.020 0.048
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.6576 0.57510 0.000 0.200 0.168 0.632
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.2882 0.71079 0.892 0.000 0.024 0.084
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.72730 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.4888 0.40154 0.412 0.000 0.588 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4643 0.44488 0.656 0.000 0.344 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.3311 0.58419 0.172 0.000 0.828 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.2469 0.73807 0.000 0.108 0.000 0.892
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.8379 0.33264 0.252 0.500 0.200 0.048
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.2002 0.79017 0.020 0.936 0.044 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.2593 0.71074 0.892 0.004 0.104 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0804 0.73116 0.980 0.000 0.008 0.012
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.6466 0.50133 0.104 0.288 0.608 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4313 0.61296 0.260 0.736 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3751 0.63953 0.196 0.800 0.000 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2647 0.69744 0.880 0.000 0.000 0.120
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.9019 0.37553 0.224 0.128 0.168 0.480
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4605 0.52996 0.336 0.000 0.664 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.4406 0.21281 0.700 0.000 0.300 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.3311 0.58419 0.172 0.000 0.828 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.4830 0.56649 0.392 0.000 0.608 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1867 0.78239 0.000 0.928 0.000 0.072
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4103 0.61209 0.744 0.000 0.256 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.4222 0.59478 0.728 0.000 0.272 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.2408 0.71158 0.896 0.000 0.104 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0188 0.72728 0.996 0.000 0.000 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.79195 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0817 0.72793 0.976 0.000 0.000 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2928 0.76796 0.012 0.880 0.108 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.4761 0.38056 0.000 0.372 0.628 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1302 0.79359 0.000 0.956 0.044 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4948 0.06546 0.560 0.000 0.440 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6503 0.04861 0.480 0.448 0.072 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4285 0.66593 0.820 0.076 0.104 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0592 0.72709 0.984 0.000 0.000 0.016
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.3264 0.4608 0.004 0.132 0.024 0.000 0.840
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.4009 0.5400 0.000 0.684 0.312 0.000 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.4273 0.0884 0.448 0.000 0.000 0.552 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 4 0.6788 0.3771 0.192 0.136 0.000 0.596 0.076
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1386 0.8448 0.016 0.000 0.952 0.000 0.032
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.3038 0.6979 0.040 0.872 0.080 0.000 0.008
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.1836 0.7004 0.932 0.000 0.036 0.000 0.032
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.4470 0.6727 0.052 0.796 0.100 0.000 0.052
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.1399 0.8459 0.028 0.000 0.952 0.000 0.020
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.6074 -0.0784 0.440 0.104 0.004 0.000 0.452
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5014 0.1937 0.536 0.000 0.432 0.000 0.032
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3772 0.6996 0.000 0.792 0.000 0.036 0.172
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5930 0.5173 0.676 0.064 0.084 0.000 0.176
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.1557 0.7521 0.052 0.000 0.000 0.940 0.008
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.2074 0.8482 0.044 0.000 0.920 0.000 0.036
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.7323 0.2776 0.208 0.476 0.000 0.048 0.268
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.1661 0.7521 0.000 0.036 0.000 0.940 0.024
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.4403 0.4913 0.000 0.560 0.004 0.000 0.436
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6660 0.3601 0.000 0.060 0.156 0.604 0.180
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.6745 0.1689 0.000 0.408 0.000 0.280 0.312
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.4448 -0.2027 0.516 0.000 0.000 0.004 0.480
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1410 0.7526 0.000 0.940 0.000 0.000 0.060
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.4270 0.3832 0.320 0.000 0.000 0.668 0.012
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.5221 0.5253 0.000 0.552 0.048 0.000 0.400
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.2278 0.8426 0.060 0.000 0.908 0.000 0.032
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.5123 0.4046 0.336 0.000 0.616 0.004 0.044
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.1121 0.7038 0.956 0.000 0.000 0.000 0.044
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.6007 0.5211 0.672 0.128 0.148 0.000 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4256 0.4936 0.000 0.564 0.000 0.000 0.436
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4823 0.4652 0.672 0.000 0.276 0.000 0.052
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.1907 0.8472 0.028 0.000 0.928 0.000 0.044
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.4305 -0.0450 0.488 0.000 0.000 0.512 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.3078 0.6526 0.848 0.132 0.000 0.004 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.1095 0.7108 0.968 0.008 0.012 0.000 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.4297 0.1543 0.472 0.000 0.000 0.528 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4429 0.5623 0.744 0.000 0.192 0.000 0.064
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2077 0.7034 0.920 0.040 0.000 0.000 0.040
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1341 0.7472 0.000 0.944 0.000 0.000 0.056
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.4747 -0.2217 0.500 0.000 0.000 0.016 0.484
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.2416 0.7083 0.012 0.100 0.000 0.888 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0290 0.8415 0.008 0.000 0.992 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.4841 0.6848 0.000 0.708 0.084 0.000 0.208
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3881 0.6364 0.812 0.128 0.008 0.000 0.052
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.3845 0.7430 0.124 0.004 0.812 0.000 0.060
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 1 0.7927 -0.0403 0.380 0.184 0.000 0.100 0.336
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4100 0.6704 0.192 0.000 0.764 0.000 0.044
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.2707 0.6915 0.000 0.100 0.000 0.876 0.024
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.2209 0.8442 0.056 0.000 0.912 0.000 0.032
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0404 0.7071 0.988 0.000 0.000 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2519 0.6628 0.884 0.000 0.000 0.100 0.016
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2329 0.7321 0.000 0.876 0.000 0.000 0.124
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.6858 0.2273 0.476 0.248 0.000 0.264 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.1907 0.8503 0.044 0.000 0.928 0.000 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 1 0.7685 0.2026 0.468 0.124 0.000 0.276 0.132
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.5102 0.3298 0.376 0.000 0.580 0.000 0.044
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1251 0.7399 0.036 0.956 0.000 0.000 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3480 0.5443 0.752 0.248 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.1282 0.7035 0.952 0.000 0.000 0.004 0.044
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.5165 0.2029 0.512 0.448 0.000 0.000 0.040
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1493 0.8450 0.028 0.000 0.948 0.000 0.024
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.2848 0.4216 0.000 0.156 0.004 0.000 0.840
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.4264 0.4484 0.732 0.008 0.012 0.004 0.244
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.1043 0.7046 0.960 0.000 0.000 0.000 0.040
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0693 0.7087 0.980 0.000 0.008 0.000 0.012
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.5002 0.4970 0.000 0.132 0.000 0.708 0.160
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.6469 0.3676 0.064 0.320 0.052 0.004 0.560
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.7434 0.000 1.000 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.4780 0.6696 0.000 0.692 0.060 0.000 0.248
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.0798 0.8436 0.008 0.000 0.976 0.000 0.016
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0771 0.8436 0.004 0.000 0.976 0.000 0.020
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.6499 0.1416 0.364 0.464 0.004 0.000 0.168
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.5233 0.5518 0.204 0.700 0.080 0.000 0.016
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1393 0.8519 0.024 0.008 0.956 0.000 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.1121 0.7038 0.956 0.000 0.000 0.000 0.044
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.4687 0.6119 0.028 0.636 0.000 0.000 0.336
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1041 0.7069 0.964 0.000 0.000 0.004 0.032
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.3160 0.6677 0.000 0.808 0.188 0.000 0.004
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 4 0.0609 0.7792 0.020 0.000 0.000 0.980 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1792 0.7416 0.000 0.916 0.000 0.000 0.084
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1012 0.7052 0.968 0.000 0.000 0.020 0.012
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0324 0.8381 0.000 0.004 0.992 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.7434 0.000 1.000 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.2209 0.8442 0.056 0.000 0.912 0.000 0.032
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0671 0.7096 0.980 0.000 0.000 0.004 0.016
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.4585 0.5412 0.000 0.628 0.000 0.020 0.352
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.1830 0.7051 0.924 0.000 0.008 0.000 0.068
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.4937 0.4189 0.176 0.100 0.004 0.000 0.720
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3291 0.7346 0.028 0.856 0.000 0.016 0.100
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.5495 0.4214 0.000 0.500 0.064 0.000 0.436
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1908 0.7414 0.000 0.908 0.000 0.000 0.092
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0693 0.7087 0.980 0.000 0.008 0.000 0.012
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.1117 0.7421 0.016 0.964 0.000 0.000 0.020
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#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.5468 0.3851 0.568 0.368 0.004 0.000 0.060
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.7426 0.3286 0.496 0.268 0.084 0.000 0.152
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0404 0.7071 0.988 0.000 0.000 0.000 0.012
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.3579 0.4847 0.240 0.756 0.000 0.004 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.4306 -0.0639 0.492 0.000 0.000 0.508 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.1430 0.7392 0.000 0.944 0.052 0.000 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0794 0.7408 0.028 0.972 0.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.1282 0.7035 0.952 0.000 0.000 0.004 0.044
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0794 0.7408 0.028 0.972 0.000 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.1403 0.8455 0.024 0.000 0.952 0.000 0.024
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.4288 0.6788 0.044 0.800 0.120 0.000 0.036
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 5 0.5998 -0.0187 0.112 0.000 0.000 0.424 0.464
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.2424 0.7291 0.000 0.868 0.000 0.000 0.132
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0963 0.7051 0.964 0.000 0.000 0.000 0.036
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4532 0.4747 0.672 0.304 0.004 0.000 0.020
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.4793 0.4801 0.000 0.544 0.020 0.000 0.436
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.6527 0.2797 0.488 0.392 0.000 0.076 0.044
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0898 0.7079 0.972 0.000 0.008 0.000 0.020
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2570 0.8033 0.084 0.000 0.888 0.000 0.028
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.1774 0.7016 0.932 0.000 0.016 0.000 0.052
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.2230 0.6637 0.884 0.000 0.000 0.116 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1671 0.7439 0.000 0.924 0.000 0.000 0.076
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.3837 0.6138 0.000 0.692 0.000 0.000 0.308
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.1493 0.8448 0.028 0.000 0.948 0.000 0.024
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.4688 0.4067 0.616 0.364 0.004 0.000 0.016
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.1753 0.8492 0.032 0.000 0.936 0.000 0.032
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0290 0.8390 0.000 0.000 0.992 0.000 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.5668 0.2054 0.504 0.000 0.416 0.000 0.080
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.1493 0.8450 0.028 0.000 0.948 0.000 0.024
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.3602 0.6656 0.000 0.796 0.180 0.000 0.024
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.2172 0.7046 0.916 0.004 0.020 0.000 0.060
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.2278 0.8426 0.060 0.000 0.908 0.000 0.032
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.1608 0.7074 0.928 0.000 0.000 0.000 0.072
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 4 0.5869 0.0890 0.004 0.428 0.000 0.484 0.084
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.2125 0.7301 0.052 0.920 0.000 0.004 0.024
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.5188 0.3957 0.328 0.000 0.612 0.000 0.060
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0566 0.8369 0.000 0.012 0.984 0.000 0.004
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.1282 0.7035 0.952 0.000 0.000 0.004 0.044
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.6037 0.3122 0.000 0.444 0.000 0.116 0.440
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.7434 0.000 1.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0404 0.7071 0.988 0.000 0.000 0.000 0.012
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.2221 0.8454 0.052 0.000 0.912 0.000 0.036
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.1582 0.8435 0.028 0.000 0.944 0.000 0.028
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0898 0.7079 0.972 0.000 0.008 0.000 0.020
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3157 0.6887 0.872 0.052 0.016 0.000 0.060
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6814 0.0508 0.188 0.520 0.000 0.024 0.268
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0912 0.7057 0.972 0.000 0.000 0.016 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.6015 0.2351 0.000 0.124 0.000 0.516 0.360
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0566 0.7081 0.984 0.000 0.000 0.012 0.004
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0703 0.7062 0.976 0.000 0.000 0.000 0.024
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.5351 0.1541 0.484 0.000 0.464 0.000 0.052
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 5 0.5227 0.2433 0.448 0.000 0.044 0.000 0.508
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.2054 0.8303 0.028 0.000 0.920 0.000 0.052
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.2074 0.7061 0.000 0.104 0.000 0.896 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.6412 0.2704 0.492 0.384 0.004 0.012 0.108
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.1043 0.7408 0.000 0.960 0.040 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.1717 0.7021 0.936 0.004 0.008 0.000 0.052
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0510 0.7077 0.984 0.000 0.000 0.000 0.016
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1082 0.7091 0.964 0.000 0.008 0.000 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0324 0.8398 0.004 0.000 0.992 0.000 0.004
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.3182 0.6723 0.124 0.844 0.000 0.000 0.032
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2929 0.5824 0.180 0.820 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0609 0.7069 0.980 0.000 0.000 0.020 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.7345 0.2031 0.472 0.076 0.000 0.320 0.132
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1668 0.8464 0.028 0.000 0.940 0.000 0.032
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.5080 0.3470 0.368 0.000 0.588 0.000 0.044
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.2304 0.8334 0.044 0.000 0.908 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1485 0.8451 0.020 0.000 0.948 0.000 0.032
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3692 0.7057 0.000 0.812 0.000 0.052 0.136
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0992 0.7082 0.968 0.000 0.008 0.000 0.024
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1557 0.7024 0.940 0.000 0.008 0.000 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.2179 0.6578 0.888 0.000 0.000 0.000 0.112
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.7886 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0865 0.7089 0.972 0.000 0.000 0.004 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2494 0.7409 0.008 0.904 0.056 0.000 0.032
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0324 0.8381 0.000 0.004 0.992 0.000 0.004
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1544 0.7477 0.000 0.932 0.000 0.000 0.068
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.5529 0.2072 0.420 0.000 0.512 0.000 0.068
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5042 0.2677 0.512 0.460 0.004 0.000 0.024
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3345 0.6757 0.864 0.060 0.024 0.000 0.052
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1282 0.7035 0.952 0.000 0.000 0.004 0.044
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.2592 0.295108 0.000 0.116 0.004 0.000 0.864 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0000 0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.5403 0.244270 0.000 0.124 0.516 0.000 0.000 0.360
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.4185 0.168569 0.496 0.012 0.000 0.492 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.4949 0.005558 0.000 0.696 0.000 0.196 0.052 0.056
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.3830 0.546730 0.004 0.000 0.620 0.000 0.000 0.376
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4629 0.595265 0.028 0.596 0.012 0.000 0.000 0.364
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2730 0.639815 0.808 0.000 0.000 0.000 0.000 0.192
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.6143 -0.186787 0.276 0.120 0.548 0.000 0.000 0.056
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.5445 0.596686 0.124 0.000 0.548 0.000 0.004 0.324
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3765 0.552191 0.000 0.404 0.000 0.000 0.596 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4873 0.262192 0.600 0.000 0.080 0.000 0.000 0.320
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3190 0.148493 0.000 0.820 0.000 0.044 0.136 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.4257 0.557416 0.652 0.000 0.320 0.000 0.016 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.2680 0.740734 0.056 0.000 0.000 0.868 0.000 0.076
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.5795 0.577804 0.184 0.000 0.452 0.000 0.000 0.364
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4045 -0.234333 0.008 0.648 0.000 0.008 0.336 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.4802 0.264266 0.000 0.404 0.000 0.540 0.000 0.056
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 5 0.3765 0.552191 0.000 0.404 0.000 0.000 0.596 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.6569 0.397786 0.000 0.132 0.028 0.552 0.244 0.044
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3975 0.094818 0.000 0.764 0.000 0.020 0.180 0.036
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.5902 0.060279 0.392 0.000 0.000 0.000 0.404 0.204
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5887 0.431910 0.000 0.404 0.000 0.000 0.200 0.396
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.5366 0.371821 0.320 0.000 0.000 0.548 0.000 0.132
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.5439 0.447470 0.000 0.260 0.008 0.000 0.592 0.140
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5842 0.571773 0.196 0.000 0.448 0.000 0.000 0.356
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3499 0.566882 0.680 0.000 0.320 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.6074 -0.057014 0.424 0.000 0.348 0.000 0.004 0.224
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2597 0.633272 0.824 0.000 0.000 0.000 0.000 0.176
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.3804 0.507483 0.576 0.000 0.424 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 5 0.3765 0.552191 0.000 0.404 0.000 0.000 0.596 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0000 0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.3938 0.557563 0.660 0.000 0.324 0.000 0.000 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.5720 0.579746 0.172 0.000 0.472 0.000 0.000 0.356
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.4808 0.309584 0.536 0.000 0.000 0.408 0.000 0.056
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.2688 0.646095 0.868 0.064 0.000 0.000 0.000 0.068
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0363 0.660971 0.988 0.000 0.012 0.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.4576 0.372364 0.400 0.000 0.000 0.560 0.000 0.040
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4348 0.557138 0.640 0.000 0.320 0.000 0.000 0.040
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1980 0.666254 0.920 0.008 0.036 0.000 0.000 0.036
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.4159 0.620981 0.000 0.588 0.000 0.000 0.016 0.396
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.6215 0.072653 0.376 0.000 0.000 0.012 0.404 0.208
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 4 0.4743 0.473142 0.012 0.280 0.000 0.652 0.000 0.056
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.3515 0.538196 0.000 0.000 0.676 0.000 0.000 0.324
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 6 0.7593 -0.046239 0.000 0.256 0.160 0.000 0.280 0.304
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3772 0.565597 0.672 0.004 0.320 0.000 0.000 0.004
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 6 0.6875 -0.400132 0.148 0.000 0.376 0.000 0.088 0.388
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.4252 -0.005973 0.000 0.728 0.000 0.032 0.216 0.024
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.3499 0.566882 0.680 0.000 0.320 0.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.6047 0.359158 0.256 0.000 0.392 0.000 0.000 0.352
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.3288 0.647418 0.000 0.176 0.000 0.800 0.008 0.016
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5442 0.592080 0.128 0.000 0.508 0.000 0.000 0.364
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1910 0.642760 0.892 0.000 0.000 0.000 0.000 0.108
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.3874 0.598811 0.760 0.000 0.000 0.068 0.000 0.172
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.4395 0.621726 0.000 0.568 0.000 0.000 0.028 0.404
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.6084 0.369171 0.560 0.304 0.000 0.064 0.016 0.056
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.5472 0.594546 0.132 0.000 0.504 0.000 0.000 0.364
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#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3499 0.566882 0.680 0.000 0.320 0.000 0.000 0.000
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#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.815106 0.000 0.000 0.000 1.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1814 0.655646 0.900 0.000 0.000 0.000 0.000 0.100
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.7391 0.138886 0.132 0.480 0.212 0.000 0.024 0.152
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3563 0.532334 0.000 0.000 0.664 0.000 0.000 0.336
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2527 0.134952 0.000 0.832 0.000 0.000 0.168 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5744 0.046239 0.476 0.000 0.344 0.000 0.000 0.180
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4500 0.333651 0.572 0.392 0.036 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.3804 0.507483 0.576 0.000 0.424 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.2854 0.622801 0.792 0.000 0.000 0.000 0.000 0.208
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.980 0.948 0.969 0.480 0.521 0.521
#> 3 3 0.617 0.666 0.841 0.245 0.902 0.813
#> 4 4 0.486 0.532 0.741 0.134 0.838 0.646
#> 5 5 0.496 0.367 0.670 0.083 0.884 0.681
#> 6 6 0.559 0.347 0.681 0.073 0.799 0.423
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.5629 0.8642 0.132 0.868
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.0938 0.9695 0.012 0.988
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.0672 0.9747 0.992 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.3114 0.9389 0.056 0.944
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0938 0.9695 0.012 0.988
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0938 0.9714 0.988 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4161 0.9149 0.084 0.916
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0376 0.9749 0.996 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0672 0.9747 0.992 0.008
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0672 0.9747 0.992 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.1414 0.9711 0.020 0.980
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0938 0.9714 0.988 0.012
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1414 0.9711 0.020 0.980
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0938 0.9735 0.988 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.2603 0.9490 0.044 0.956
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0672 0.9747 0.992 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0938 0.9695 0.012 0.988
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.1414 0.9711 0.020 0.980
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0938 0.9695 0.012 0.988
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.1414 0.9711 0.020 0.980
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.1184 0.9666 0.016 0.984
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1184 0.9666 0.016 0.984
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.1184 0.9722 0.984 0.016
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1184 0.9693 0.016 0.984
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0938 0.9728 0.988 0.012
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.1414 0.9711 0.020 0.980
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0938 0.9714 0.988 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0938 0.9742 0.988 0.012
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0938 0.9714 0.988 0.012
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0938 0.9714 0.988 0.012
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0672 0.9747 0.992 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.1414 0.9711 0.020 0.980
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0938 0.9695 0.012 0.988
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0672 0.9747 0.992 0.008
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0672 0.9747 0.992 0.008
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.1184 0.9681 0.016 0.984
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.9393 0.4551 0.356 0.644
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0938 0.9742 0.988 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0938 0.9728 0.988 0.012
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.0938 0.9695 0.012 0.988
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0672 0.9747 0.992 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0938 0.9714 0.988 0.012
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1184 0.9666 0.016 0.984
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0938 0.9728 0.988 0.012
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0672 0.9647 0.008 0.992
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.9745 1.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.1414 0.9711 0.020 0.980
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0938 0.9742 0.988 0.012
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0938 0.9714 0.988 0.012
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1414 0.9711 0.020 0.980
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0938 0.9742 0.988 0.012
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0938 0.9714 0.988 0.012
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.1633 0.9709 0.024 0.976
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0938 0.9714 0.988 0.012
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.1184 0.9729 0.984 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.4690 0.9001 0.900 0.100
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1184 0.9666 0.016 0.984
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0938 0.9695 0.012 0.988
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0000 0.9745 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.1184 0.9705 0.016 0.984
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1184 0.9710 0.984 0.016
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1414 0.9711 0.020 0.980
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0938 0.9736 0.988 0.012
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.1184 0.9710 0.984 0.016
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0672 0.9743 0.992 0.008
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0672 0.9747 0.992 0.008
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.1414 0.9711 0.020 0.980
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.1633 0.9693 0.976 0.024
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.1184 0.9710 0.984 0.016
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.1184 0.9729 0.984 0.016
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1414 0.9711 0.020 0.980
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.9933 0.1880 0.452 0.548
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.1414 0.9711 0.020 0.980
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.1414 0.9711 0.020 0.980
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.0938 0.9714 0.988 0.012
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.0938 0.9695 0.012 0.988
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0938 0.9714 0.988 0.012
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.7528 0.7511 0.216 0.784
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.0938 0.9714 0.988 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.0938 0.9714 0.988 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.1184 0.9710 0.984 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.1414 0.9711 0.020 0.980
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1633 0.9693 0.976 0.024
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.0672 0.9747 0.992 0.008
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.7139 0.7756 0.804 0.196
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1184 0.9666 0.016 0.984
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.1184 0.9729 0.984 0.016
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.0672 0.9747 0.992 0.008
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0938 0.9742 0.988 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1184 0.9666 0.016 0.984
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0938 0.9742 0.988 0.012
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.0938 0.9714 0.988 0.012
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.1414 0.9706 0.980 0.020
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.1414 0.9711 0.020 0.980
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0672 0.9747 0.992 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.1414 0.9711 0.020 0.980
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.1184 0.9705 0.016 0.984
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.1414 0.9711 0.020 0.980
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 2 0.0938 0.9695 0.012 0.988
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1414 0.9711 0.020 0.980
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0938 0.9742 0.988 0.012
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.1184 0.9729 0.984 0.016
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.1184 0.9708 0.984 0.016
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.1414 0.9711 0.020 0.980
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.1184 0.9729 0.984 0.016
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.0672 0.9747 0.992 0.008
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.4815 0.8869 0.896 0.104
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0938 0.9714 0.988 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1414 0.9711 0.020 0.980
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.9983 0.0753 0.524 0.476
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6973 0.7821 0.188 0.812
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0938 0.9660 0.012 0.988
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.1184 0.9666 0.016 0.984
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.0938 0.9714 0.988 0.012
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.0938 0.9695 0.012 0.988
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.1414 0.9711 0.020 0.980
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0672 0.9747 0.992 0.008
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1414 0.9711 0.020 0.980
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.0672 0.9747 0.992 0.008
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.1184 0.9708 0.984 0.016
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0938 0.9742 0.988 0.012
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.1184 0.9729 0.984 0.016
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0938 0.9660 0.012 0.988
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#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1414 0.9711 0.020 0.980
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0938 0.9714 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0672 0.9747 0.992 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0938 0.9742 0.988 0.012
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1414 0.9698 0.980 0.020
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.2774 0.826048 0.072 0.920 0.008
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.6309 -0.159321 0.500 0.500 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3619 0.797254 0.136 0.000 0.864
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.6824 0.134828 0.576 0.408 0.016
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1529 0.852464 0.040 0.960 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0424 0.836314 0.008 0.000 0.992
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.9421 0.425633 0.436 0.388 0.176
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0424 0.834898 0.008 0.000 0.992
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.2066 0.827073 0.060 0.000 0.940
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.2448 0.830292 0.076 0.000 0.924
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.2356 0.831813 0.072 0.928 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0424 0.834898 0.008 0.000 0.992
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0237 0.868166 0.004 0.996 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.5538 0.740921 0.132 0.060 0.808
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.8058 0.464346 0.640 0.236 0.124
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0000 0.835249 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.6309 0.138053 0.500 0.500 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0237 0.867987 0.004 0.996 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2537 0.823900 0.080 0.920 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0424 0.867239 0.008 0.992 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.868795 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.868795 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 3 0.3192 0.804499 0.112 0.000 0.888
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.868795 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.4974 0.413303 0.764 0.000 0.236
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0424 0.867239 0.008 0.992 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.6111 0.450571 0.396 0.000 0.604
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.3038 0.805619 0.104 0.000 0.896
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.2066 0.827764 0.060 0.000 0.940
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.0424 0.834898 0.008 0.000 0.992
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.1753 0.822895 0.048 0.000 0.952
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0424 0.867239 0.008 0.992 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.6309 -0.159321 0.500 0.500 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.0592 0.834829 0.012 0.000 0.988
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.0424 0.834820 0.008 0.000 0.992
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.6126 0.374636 0.400 0.600 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.9252 0.450367 0.480 0.356 0.164
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.2448 0.821282 0.076 0.000 0.924
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.5988 0.433742 0.368 0.000 0.632
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.6309 0.138053 0.500 0.500 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.0592 0.835404 0.012 0.000 0.988
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.3551 0.791482 0.132 0.000 0.868
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.868795 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 3 0.4062 0.769099 0.164 0.000 0.836
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.8935 -0.088167 0.424 0.452 0.124
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1411 0.828248 0.036 0.000 0.964
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0424 0.867239 0.008 0.992 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.3267 0.799979 0.116 0.000 0.884
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 3 0.5948 0.517876 0.360 0.000 0.640
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.1411 0.853104 0.036 0.964 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.1031 0.836782 0.024 0.000 0.976
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.0592 0.835405 0.012 0.000 0.988
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0000 0.868795 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.2878 0.808221 0.096 0.000 0.904
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.5254 0.539143 0.264 0.000 0.736
#> 311D089C-33F1-4722-9118-F56427C5C128 3 0.6520 0.230958 0.488 0.004 0.508
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.868795 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.1860 0.845379 0.052 0.948 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0747 0.833807 0.016 0.000 0.984
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.868795 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.0747 0.835880 0.016 0.000 0.984
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.868795 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.5845 0.600146 0.308 0.004 0.688
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.3340 0.798687 0.120 0.000 0.880
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.5016 0.689449 0.240 0.000 0.760
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.1163 0.836034 0.028 0.000 0.972
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.2356 0.831451 0.072 0.928 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.6280 0.315300 0.460 0.000 0.540
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.0237 0.835239 0.004 0.000 0.996
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.2537 0.820594 0.080 0.000 0.920
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.868795 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.8628 0.039853 0.472 0.100 0.428
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.868795 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0424 0.867239 0.008 0.992 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.5968 0.468733 0.364 0.000 0.636
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.6309 -0.159321 0.500 0.500 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.1643 0.824807 0.044 0.000 0.956
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.8579 -0.269550 0.440 0.464 0.096
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1529 0.829918 0.040 0.000 0.960
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.6095 0.491029 0.392 0.000 0.608
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.5785 0.564237 0.332 0.000 0.668
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0424 0.867239 0.008 0.992 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 3 0.6451 0.363331 0.436 0.004 0.560
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.6079 0.508846 0.388 0.000 0.612
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.4842 0.426804 0.776 0.000 0.224
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.868795 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.5859 0.462527 0.344 0.000 0.656
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.1643 0.824807 0.044 0.000 0.956
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0424 0.835025 0.008 0.000 0.992
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.3038 0.766576 0.104 0.896 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.0892 0.833005 0.020 0.000 0.980
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.0592 0.836011 0.012 0.000 0.988
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 3 0.4235 0.754046 0.176 0.000 0.824
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.868795 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.0424 0.834898 0.008 0.000 0.992
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.2356 0.831813 0.072 0.928 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.868795 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0424 0.867239 0.008 0.992 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.6309 -0.159321 0.500 0.500 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.868795 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.0747 0.837227 0.016 0.000 0.984
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.0000 0.835249 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.9108 0.113794 0.444 0.140 0.416
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0237 0.867987 0.004 0.996 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.0237 0.835239 0.004 0.000 0.996
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.6500 0.316562 0.464 0.004 0.532
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.8688 0.004325 0.460 0.104 0.436
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0424 0.834820 0.008 0.000 0.992
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0237 0.868166 0.004 0.996 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 3 0.7571 0.224804 0.452 0.040 0.508
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.6737 0.166660 0.384 0.600 0.016
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.2261 0.823386 0.068 0.932 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.868795 0.000 1.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 3 0.4062 0.766662 0.164 0.000 0.836
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.2625 0.821059 0.084 0.916 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0424 0.867239 0.008 0.992 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.0592 0.836257 0.012 0.000 0.988
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.868795 0.000 1.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.1753 0.822895 0.048 0.000 0.952
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 3 0.6244 0.358500 0.440 0.000 0.560
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.1643 0.824807 0.044 0.000 0.956
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 3 0.5591 0.518883 0.304 0.000 0.696
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0237 0.867791 0.004 0.996 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.5098 0.683458 0.248 0.000 0.752
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.1163 0.859531 0.028 0.972 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.6302 -0.127535 0.520 0.480 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.8814 0.343790 0.480 0.404 0.116
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.5905 0.529788 0.352 0.000 0.648
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 3 0.0592 0.836400 0.012 0.000 0.988
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.1289 0.855948 0.032 0.968 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.0424 0.834898 0.008 0.000 0.992
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0237 0.868166 0.004 0.996 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.1964 0.828787 0.056 0.000 0.944
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.1031 0.834984 0.024 0.000 0.976
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 3 0.0424 0.834898 0.008 0.000 0.992
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.3038 0.811450 0.104 0.000 0.896
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 2 0.6309 0.138053 0.500 0.500 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.3941 0.695690 0.156 0.844 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 3 0.4504 0.743929 0.196 0.000 0.804
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0424 0.867239 0.008 0.992 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.1753 0.822895 0.048 0.000 0.952
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.7192 0.366366 0.412 0.028 0.560
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.868795 0.000 1.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.1643 0.836211 0.044 0.956 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 3 0.3340 0.808826 0.120 0.000 0.880
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.868795 0.000 1.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0237 0.868166 0.004 0.996 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 3 0.2165 0.823624 0.064 0.000 0.936
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0747 0.833807 0.016 0.000 0.984
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.6026 0.176371 0.624 0.000 0.376
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0237 0.867987 0.004 0.996 0.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.1643 0.824807 0.044 0.000 0.956
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 3 0.1860 0.824604 0.052 0.000 0.948
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 3 0.4605 0.732756 0.204 0.000 0.796
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 3 0.5988 0.503097 0.368 0.000 0.632
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 3 0.6267 0.334173 0.452 0.000 0.548
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 3 0.0747 0.835366 0.016 0.000 0.984
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 3 0.0747 0.836262 0.016 0.000 0.984
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F 2 0.4887 0.658283 0.228 0.772 0.000
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0 2 0.0000 0.868795 0.000 1.000 0.000
#> D149276E-A961-49D6-8BDA-004E8264A0A1 3 0.0592 0.837058 0.012 0.000 0.988
#> D17803A2-4BF2-4382-A544-76E28695214F 1 0.6215 0.061341 0.572 0.000 0.428
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6 3 0.0892 0.835533 0.020 0.000 0.980
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#> 97FB3176-395F-475B-8EAE-332C5BEE8155 3 0.1289 0.833395 0.032 0.000 0.968
#> E1876307-DFD9-4688-876F-D71B37466068 2 0.0424 0.867239 0.008 0.992 0.000
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04 2 0.7782 0.229164 0.248 0.652 0.100
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00 2 0.6309 0.138053 0.500 0.500 0.000
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79 3 0.2959 0.804980 0.100 0.000 0.900
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 3 0.1289 0.834778 0.032 0.000 0.968
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 3 0.5948 0.517068 0.360 0.000 0.640
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 3 0.1643 0.824807 0.044 0.000 0.956
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 3 0.1643 0.824807 0.044 0.000 0.956
#> B3CCA12D-4569-4AB8-AC41-457448268D90 3 0.5988 0.433289 0.368 0.000 0.632
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 3 0.6244 0.357141 0.440 0.000 0.560
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 3 0.2066 0.824095 0.060 0.000 0.940
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.0000 0.868795 0.000 1.000 0.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 3 0.0237 0.835239 0.004 0.000 0.996
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0424 0.867239 0.008 0.992 0.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.868795 0.000 1.000 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 3 0.7517 0.297724 0.420 0.040 0.540
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 3 0.5621 0.601968 0.308 0.000 0.692
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.868795 0.000 1.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 3 0.5178 0.672292 0.256 0.000 0.744
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.1964 0.822825 0.056 0.000 0.944
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.1031 0.832108 0.024 0.000 0.976
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.2448 0.820498 0.076 0.000 0.924
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.3340 0.796880 0.120 0.000 0.880
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0237 0.867987 0.004 0.996 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0424 0.867239 0.008 0.992 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.4178 0.757833 0.172 0.000 0.828
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.2356 0.831451 0.072 0.928 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.3686 0.799795 0.140 0.000 0.860
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 3 0.6309 0.174813 0.496 0.000 0.504
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0424 0.867239 0.008 0.992 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 3 0.0424 0.834898 0.008 0.000 0.992
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.1411 0.828602 0.036 0.000 0.964
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 3 0.1411 0.834342 0.036 0.000 0.964
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0237 0.868166 0.004 0.996 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.1753 0.826787 0.048 0.000 0.952
#> 34ED910C-7470-4552-8561-D01D59190521 3 0.2066 0.824540 0.060 0.000 0.940
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.8574 0.121861 0.432 0.096 0.472
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.6309 -0.159321 0.500 0.500 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.2448 0.831200 0.076 0.924 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.868795 0.000 1.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.1753 0.822895 0.048 0.000 0.952
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.8582 -0.269507 0.452 0.452 0.096
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.4589 0.657795 0.172 0.820 0.008
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0424 0.866113 0.008 0.992 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.6379 0.389451 0.368 0.624 0.008
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.5098 0.522322 0.248 0.752 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 3 0.3879 0.777842 0.152 0.000 0.848
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 3 0.6215 0.332962 0.428 0.000 0.572
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.2165 0.823049 0.064 0.000 0.936
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.6267 0.334173 0.452 0.000 0.548
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.2261 0.828453 0.068 0.000 0.932
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.868795 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.2261 0.831626 0.068 0.932 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0424 0.867239 0.008 0.992 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0424 0.867239 0.008 0.992 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.6309 -0.159321 0.500 0.500 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.3715 0.791084 0.128 0.004 0.868
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.0424 0.834898 0.008 0.000 0.992
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 3 0.3267 0.802098 0.116 0.000 0.884
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.868795 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0424 0.834898 0.008 0.000 0.992
#> 17CA5D73-4384-4645-83F8-587847043DD2 3 0.5327 0.587254 0.272 0.000 0.728
#> 40467950-A95C-4731-AD93-0A128442C837 3 0.2356 0.822832 0.072 0.000 0.928
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 3 0.4931 0.716062 0.212 0.004 0.784
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.3879 0.774702 0.152 0.000 0.848
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.1860 0.820989 0.052 0.000 0.948
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.1753 0.822895 0.048 0.000 0.952
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.6309 -0.159321 0.500 0.500 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.9159 0.448263 0.508 0.328 0.164
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 3 0.2959 0.809967 0.100 0.000 0.900
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.868795 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.6274 0.304699 0.456 0.000 0.544
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0892 0.833159 0.020 0.000 0.980
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0747 0.833807 0.016 0.000 0.984
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.6302 -0.127655 0.520 0.000 0.480
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.3116 0.812070 0.108 0.000 0.892
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.8743 -0.000782 0.440 0.108 0.452
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 3 0.0747 0.835643 0.016 0.000 0.984
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.2625 0.821059 0.084 0.916 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.6266 0.515152 0.768 0.076 0.156
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0237 0.867443 0.004 0.996 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.868795 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.5327 0.655762 0.272 0.000 0.728
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.1529 0.840666 0.040 0.960 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.1031 0.832108 0.024 0.000 0.976
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.2261 0.825481 0.068 0.000 0.932
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 3 0.4931 0.703505 0.232 0.000 0.768
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.868795 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.6309 0.138053 0.500 0.500 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0747 0.835643 0.016 0.000 0.984
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.4702 0.720676 0.212 0.000 0.788
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0424 0.867239 0.008 0.992 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0892 0.862021 0.020 0.980 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.0000 0.835249 0.000 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.1289 0.829838 0.032 0.000 0.968
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.1163 0.837893 0.028 0.000 0.972
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.6286 -0.084116 0.536 0.000 0.464
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.868795 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0237 0.868166 0.004 0.996 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.6309 -0.159321 0.500 0.500 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.1753 0.822895 0.048 0.000 0.952
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.5529 0.618456 0.296 0.000 0.704
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.0592 0.836635 0.012 0.000 0.988
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1753 0.822895 0.048 0.000 0.952
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.1860 0.827653 0.052 0.000 0.948
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.1529 0.826919 0.040 0.000 0.960
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.7672 0.215089 0.468 0.044 0.488
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.1411 0.828263 0.036 0.000 0.964
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.0424 0.834898 0.008 0.000 0.992
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0424 0.834898 0.008 0.000 0.992
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.2448 0.826739 0.076 0.924 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.9560 0.338302 0.464 0.212 0.324
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.0892 0.835365 0.020 0.000 0.980
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.7744 0.219574 0.448 0.048 0.504
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.2711 0.817771 0.088 0.000 0.912
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.1643 0.853220 0.044 0.956 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.868795 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.5905 0.455347 0.352 0.000 0.648
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0592 0.835405 0.012 0.000 0.988
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.1289 0.829602 0.032 0.000 0.968
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.2959 0.789464 0.100 0.000 0.900
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0424 0.834820 0.008 0.000 0.992
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.2537 0.823900 0.080 0.920 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3983 0.372019 0.852 0.144 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.6307 -0.139059 0.512 0.488 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.4750 0.679219 0.216 0.000 0.784
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.2537 0.823900 0.080 0.920 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 3 0.2796 0.815185 0.092 0.000 0.908
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.0592 0.834994 0.012 0.000 0.988
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.1643 0.825018 0.044 0.000 0.956
#> 1122039D-5785-4F70-9916-17C585453512 2 0.6309 0.138053 0.500 0.500 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 3 0.1753 0.829053 0.048 0.000 0.952
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.0892 0.833431 0.020 0.000 0.980
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.4702 0.654339 0.212 0.788 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0892 0.861204 0.020 0.980 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.8820 -0.271142 0.408 0.476 0.116
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.2796 0.811650 0.092 0.000 0.908
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.6309 0.138053 0.500 0.500 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.0000 0.835249 0.000 0.000 1.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.0424 0.834898 0.008 0.000 0.992
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1753 0.826201 0.048 0.000 0.952
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.6386 0.409608 0.412 0.004 0.584
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.868795 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.6244 0.301478 0.440 0.000 0.560
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2066 0.839266 0.060 0.940 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0747 0.833807 0.016 0.000 0.984
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.0424 0.834898 0.008 0.000 0.992
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.1753 0.831104 0.048 0.000 0.952
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1031 0.837569 0.024 0.000 0.976
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.868795 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.0424 0.834898 0.008 0.000 0.992
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.0747 0.835832 0.016 0.000 0.984
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.0892 0.833595 0.020 0.000 0.980
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.0892 0.835533 0.020 0.000 0.980
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.6309 -0.159321 0.500 0.500 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0592 0.835405 0.012 0.000 0.988
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4810 0.660591 0.140 0.832 0.028
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.7759 0.175865 0.476 0.048 0.476
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.868795 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.0747 0.835582 0.016 0.000 0.984
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.6244 0.357141 0.440 0.000 0.560
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.1753 0.822895 0.048 0.000 0.952
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.4399 0.746296 0.188 0.000 0.812
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.4284 0.60373 0.224 0.764 0.000 0.012
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.4134 0.92109 0.000 0.260 0.000 0.740
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4795 0.43059 0.292 0.000 0.696 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.8732 -0.29268 0.384 0.316 0.040 0.260
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#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4164 0.92058 0.000 0.264 0.000 0.736
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.5036 0.54968 0.280 0.000 0.696 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5564 0.51608 0.232 0.712 0.012 0.044
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.6767 0.40835 0.548 0.080 0.364 0.008
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1059 0.82904 0.012 0.972 0.000 0.016
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.5137 0.52737 0.296 0.000 0.680 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4621 0.44836 0.708 0.008 0.284 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4963 0.43738 0.284 0.000 0.696 0.020
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5650 0.08447 0.544 0.000 0.432 0.024
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.5877 -0.04961 0.016 0.348 0.000 0.072 0.564
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.5779 0.45590 0.148 0.000 0.628 0.004 0.220
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5809 0.41738 0.280 0.028 0.044 0.636 0.012
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.6396 0.18659 0.000 0.452 0.000 0.376 0.172
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.4748 0.48526 0.300 0.000 0.660 0.000 0.040
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.5375 -0.01306 0.380 0.568 0.008 0.000 0.044
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.3967 0.53540 0.264 0.000 0.724 0.000 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3994 0.48962 0.040 0.000 0.772 0.000 0.188
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.5265 0.33967 0.248 0.000 0.656 0.000 0.096
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.5694 0.05466 0.000 0.460 0.000 0.080 0.460
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.4451 0.46630 0.340 0.000 0.644 0.000 0.016
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.5684 0.17043 0.000 0.488 0.000 0.080 0.432
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.4552 0.18664 0.352 0.004 0.632 0.000 0.012
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.7277 0.00588 0.464 0.176 0.000 0.312 0.048
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.3319 0.58178 0.160 0.000 0.820 0.000 0.020
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.5684 0.17043 0.000 0.488 0.000 0.080 0.432
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.6658 0.17774 0.000 0.444 0.000 0.264 0.292
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.5680 0.15528 0.000 0.492 0.000 0.080 0.428
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.3538 0.41290 0.020 0.848 0.000 0.044 0.088
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.5192 0.31441 0.000 0.644 0.000 0.076 0.280
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2426 0.53884 0.900 0.000 0.064 0.000 0.036
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.4373 0.39688 0.000 0.760 0.000 0.080 0.160
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3656 0.54790 0.844 0.000 0.024 0.080 0.052
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.5203 0.33409 0.000 0.648 0.000 0.080 0.272
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.5474 0.20397 0.576 0.000 0.348 0.000 0.076
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4449 0.16899 0.512 0.000 0.484 0.000 0.004
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4815 -0.06165 0.524 0.000 0.456 0.000 0.020
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 3 0.4435 0.47406 0.336 0.000 0.648 0.000 0.016
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2674 0.54548 0.012 0.000 0.868 0.000 0.120
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.5684 0.16692 0.000 0.488 0.000 0.080 0.432
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.1753 0.58192 0.032 0.000 0.936 0.000 0.032
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.2561 0.59500 0.096 0.000 0.884 0.000 0.020
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.7504 0.11110 0.188 0.292 0.000 0.456 0.064
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.3663 0.44822 0.776 0.208 0.000 0.000 0.016
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.4288 0.14926 0.384 0.000 0.612 0.000 0.004
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3549 0.54817 0.852 0.000 0.032 0.076 0.040
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.2583 0.74520 0.000 0.004 0.000 0.864 0.132
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.3421 0.48602 0.204 0.000 0.788 0.000 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4276 0.18479 0.616 0.000 0.380 0.000 0.004
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.41902 0.000 1.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.3496 0.52555 0.788 0.000 0.012 0.000 0.200
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.7034 -0.13760 0.368 0.332 0.000 0.292 0.008
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.4527 0.56089 0.204 0.000 0.732 0.000 0.064
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.5203 0.33409 0.000 0.648 0.000 0.080 0.272
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.4367 0.07481 0.416 0.000 0.580 0.000 0.004
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.5616 0.12187 0.552 0.000 0.364 0.000 0.084
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.5828 0.18641 0.000 0.520 0.000 0.100 0.380
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.3863 0.45162 0.200 0.000 0.772 0.000 0.028
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4437 0.48072 0.316 0.000 0.664 0.000 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.5715 0.21620 0.000 0.524 0.000 0.088 0.388
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.5126 0.46936 0.300 0.000 0.636 0.000 0.064
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.6032 0.08511 0.476 0.000 0.436 0.072 0.016
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2366 0.55749 0.908 0.004 0.016 0.004 0.068
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.4233 0.36967 0.000 0.748 0.000 0.044 0.208
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6363 0.17702 0.000 0.444 0.000 0.392 0.164
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.4342 0.53981 0.232 0.000 0.728 0.000 0.040
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.6024 0.16191 0.000 0.472 0.000 0.116 0.412
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.4829 0.17187 0.484 0.000 0.496 0.000 0.020
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.5354 0.35091 0.000 0.664 0.000 0.128 0.208
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.2139 0.55304 0.916 0.000 0.052 0.000 0.032
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4649 0.11828 0.580 0.000 0.404 0.000 0.016
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.4697 0.19030 0.592 0.000 0.388 0.000 0.020
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.3055 0.57537 0.072 0.000 0.864 0.000 0.064
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.5689 0.09726 0.000 0.480 0.000 0.080 0.440
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3530 0.52600 0.784 0.000 0.012 0.000 0.204
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.4387 0.46538 0.348 0.000 0.640 0.000 0.012
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.6017 -0.15443 0.436 0.000 0.480 0.064 0.020
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.5718 0.18456 0.000 0.496 0.000 0.084 0.420
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.6608 -0.05240 0.276 0.492 0.004 0.000 0.228
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.3471 0.41858 0.000 0.836 0.000 0.072 0.092
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.5203 0.33409 0.000 0.648 0.000 0.080 0.272
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.6587 0.36023 0.332 0.024 0.528 0.004 0.112
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.5551 0.48261 0.284 0.000 0.612 0.000 0.104
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.8875 -0.18412 0.332 0.348 0.144 0.056 0.120
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.4823 0.49318 0.316 0.000 0.644 0.000 0.040
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.6377 0.00951 0.484 0.000 0.336 0.000 0.180
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.3988 0.40801 0.732 0.000 0.252 0.000 0.016
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.5203 0.33409 0.000 0.648 0.000 0.080 0.272
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1943 0.54974 0.924 0.000 0.056 0.000 0.020
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.6626 0.06224 0.332 0.000 0.464 0.004 0.200
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.3516 0.54325 0.836 0.000 0.004 0.108 0.052
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0404 0.41659 0.000 0.988 0.000 0.000 0.012
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.5330 0.44041 0.668 0.000 0.248 0.072 0.012
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4054 0.50707 0.036 0.000 0.760 0.000 0.204
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.3845 0.50448 0.208 0.000 0.768 0.000 0.024
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0609 0.41162 0.000 0.980 0.000 0.000 0.020
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.2054 0.58093 0.052 0.000 0.920 0.000 0.028
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.4603 0.48895 0.300 0.000 0.668 0.000 0.032
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.3419 0.48453 0.804 0.000 0.180 0.000 0.016
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.5680 0.17393 0.000 0.492 0.000 0.080 0.428
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.2193 0.58713 0.092 0.000 0.900 0.000 0.008
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.5691 -0.14970 0.000 0.444 0.000 0.080 0.476
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.5805 0.32376 0.000 0.612 0.000 0.172 0.216
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.5693 0.08678 0.000 0.468 0.000 0.080 0.452
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.5181 0.34046 0.000 0.652 0.000 0.080 0.268
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.3650 0.49420 0.176 0.000 0.796 0.000 0.028
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.3690 0.52660 0.200 0.000 0.780 0.000 0.020
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.5854 0.29569 0.596 0.012 0.300 0.000 0.092
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.5158 0.33985 0.000 0.656 0.000 0.080 0.264
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.3231 0.53600 0.196 0.000 0.800 0.000 0.004
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 3 0.6630 0.07916 0.316 0.000 0.472 0.004 0.208
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.6568 0.23278 0.496 0.000 0.336 0.012 0.156
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.4213 0.49018 0.308 0.000 0.680 0.000 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.5680 0.17393 0.000 0.492 0.000 0.080 0.428
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.5822 0.41522 0.640 0.012 0.000 0.132 0.216
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.7974 -0.02649 0.212 0.520 0.116 0.120 0.032
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.3053 0.37995 0.008 0.852 0.000 0.128 0.012
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.2966 0.36416 0.000 0.816 0.000 0.000 0.184
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.5473 -0.00262 0.520 0.000 0.416 0.000 0.064
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.6458 0.16035 0.000 0.424 0.000 0.396 0.180
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.5181 0.33672 0.000 0.652 0.000 0.080 0.268
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 3 0.4119 0.48365 0.212 0.000 0.752 0.000 0.036
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.5158 0.34094 0.000 0.656 0.000 0.080 0.264
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.3209 0.50330 0.008 0.000 0.812 0.000 0.180
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.3586 0.52906 0.792 0.000 0.020 0.000 0.188
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.3593 0.58131 0.088 0.000 0.828 0.000 0.084
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.5967 0.30576 0.528 0.000 0.384 0.072 0.016
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.3734 0.36408 0.000 0.796 0.000 0.036 0.168
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 3 0.6476 -0.05990 0.312 0.000 0.480 0.000 0.208
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.5691 0.08282 0.000 0.476 0.000 0.080 0.444
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.0960 0.85977 0.016 0.004 0.000 0.972 0.008
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.5342 -0.05158 0.464 0.496 0.000 0.024 0.016
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.5509 0.18108 0.564 0.000 0.360 0.000 0.076
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 3 0.4380 0.37359 0.304 0.000 0.676 0.000 0.020
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.5288 0.34696 0.000 0.656 0.000 0.100 0.244
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.3246 0.57460 0.184 0.000 0.808 0.000 0.008
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.5689 0.15498 0.000 0.480 0.000 0.080 0.440
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.4541 0.50877 0.112 0.000 0.752 0.000 0.136
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.4418 0.47713 0.332 0.000 0.652 0.000 0.016
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 3 0.4443 0.23522 0.472 0.000 0.524 0.000 0.004
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.4824 0.47547 0.076 0.000 0.720 0.004 0.200
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.8160 -0.05134 0.256 0.444 0.012 0.112 0.176
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.3009 0.54596 0.876 0.000 0.052 0.064 0.008
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.5680 0.17393 0.000 0.492 0.000 0.080 0.428
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.3231 0.49379 0.004 0.000 0.800 0.000 0.196
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.6582 0.01055 0.356 0.000 0.456 0.004 0.184
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#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.8444 0.27279 0.388 0.204 0.216 0.004 0.188
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4752 0.08473 0.568 0.000 0.412 0.000 0.020
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.5693 0.13455 0.000 0.468 0.000 0.080 0.452
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0404 0.41764 0.000 0.988 0.000 0.000 0.012
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3065 0.54384 0.872 0.000 0.048 0.072 0.008
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.4445 0.48909 0.300 0.000 0.676 0.000 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2230 0.58955 0.044 0.000 0.912 0.000 0.044
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.5780 0.26076 0.508 0.000 0.420 0.060 0.012
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.2674 0.59059 0.140 0.000 0.856 0.000 0.004
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.6632 0.16311 0.000 0.428 0.000 0.344 0.228
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.1728 0.82767 0.036 0.004 0.000 0.940 0.020
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.5305 0.45678 0.672 0.000 0.244 0.072 0.012
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.6495 0.19658 0.000 0.480 0.000 0.304 0.216
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.5419 0.41520 0.640 0.000 0.284 0.064 0.012
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.4448 0.28191 0.480 0.000 0.516 0.000 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.1792 0.56348 0.000 0.000 0.916 0.000 0.084
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.5783 0.16233 0.540 0.000 0.360 0.000 0.100
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.2221 0.58110 0.052 0.000 0.912 0.000 0.036
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.6633 -0.21321 0.000 0.220 0.000 0.396 0.384
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.5700 0.22659 0.000 0.532 0.000 0.088 0.380
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.5543 0.01919 0.320 0.612 0.024 0.000 0.044
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4446 0.18692 0.520 0.000 0.476 0.000 0.004
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.3715 0.48562 0.260 0.000 0.736 0.000 0.004
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.3495 0.54064 0.160 0.000 0.812 0.000 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.5968 0.45492 0.268 0.000 0.576 0.000 0.156
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4219 0.39616 0.716 0.000 0.260 0.000 0.024
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5659 0.33216 0.000 0.632 0.000 0.204 0.164
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.5685 0.43368 0.656 0.000 0.240 0.076 0.028
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.6498 0.18926 0.000 0.452 0.000 0.352 0.196
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.1732 0.59505 0.080 0.000 0.920 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.4508 0.47156 0.332 0.000 0.648 0.000 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.4589 0.35775 0.248 0.000 0.704 0.000 0.048
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.5068 0.47276 0.300 0.000 0.640 0.000 0.060
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.6351 0.21863 0.000 0.508 0.000 0.192 0.300
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.3841 0.50687 0.188 0.000 0.780 0.000 0.032
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.3650 0.48123 0.176 0.000 0.796 0.000 0.028
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.1997 0.57737 0.036 0.000 0.924 0.000 0.040
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.4610 0.33500 0.432 0.000 0.556 0.000 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0162 0.87850 0.000 0.004 0.000 0.996 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.4505 0.41724 0.384 0.000 0.604 0.000 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 5 0.8397 0.19749 0.244 0.256 0.024 0.080 0.396
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 5 0.7811 -0.41343 0.324 0.008 0.284 0.040 0.344
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.5136 0.34286 0.000 0.660 0.000 0.080 0.260
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.4890 -0.08487 0.524 0.000 0.452 0.000 0.024
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.3708 0.53881 0.816 0.000 0.136 0.004 0.044
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4022 0.50530 0.100 0.000 0.796 0.000 0.104
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.3224 0.50086 0.824 0.000 0.160 0.000 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.3864 1.72e-01 0.000 0.520 0.000 0.000 0.480 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4165 3.86e-01 0.420 0.000 0.568 0.004 0.000 0.008
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.1959 8.17e-01 0.000 0.032 0.020 0.924 0.000 0.024
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.5854 -1.05e-01 0.000 0.416 0.000 0.392 0.192 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0547 4.98e-01 0.980 0.000 0.020 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 5 0.6598 4.84e-01 0.012 0.296 0.056 0.004 0.520 0.112
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4469 4.30e-01 0.736 0.000 0.128 0.000 0.012 0.124
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3330 5.74e-01 0.284 0.000 0.716 0.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.4086 3.62e-01 0.464 0.000 0.528 0.000 0.000 0.008
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3464 3.70e-01 0.000 0.688 0.000 0.000 0.312 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2518 5.19e-01 0.880 0.000 0.016 0.000 0.012 0.092
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1444 5.57e-01 0.000 0.928 0.000 0.000 0.072 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 3 0.6590 3.23e-01 0.312 0.000 0.464 0.000 0.056 0.168
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.7263 2.63e-01 0.000 0.148 0.012 0.428 0.108 0.304
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.3200 3.31e-01 0.788 0.000 0.196 0.000 0.000 0.016
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0713 5.72e-01 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.6068 -2.46e-01 0.000 0.364 0.000 0.372 0.264 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2597 4.88e-01 0.000 0.824 0.000 0.000 0.176 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.4408 -3.15e-02 0.000 0.644 0.004 0.012 0.324 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 5 0.3789 4.21e-01 0.000 0.416 0.000 0.000 0.584 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.4616 6.43e-01 0.124 0.000 0.092 0.000 0.040 0.744
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2562 4.02e-01 0.000 0.828 0.000 0.000 0.172 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.2065 6.61e-01 0.052 0.000 0.000 0.032 0.004 0.912
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.4120 4.62e-01 0.776 0.000 0.044 0.000 0.040 0.140
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.6680 1.82e-01 0.204 0.000 0.388 0.000 0.044 0.364
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.4007 4.79e-01 0.756 0.000 0.024 0.000 0.028 0.192
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2443 5.18e-01 0.880 0.000 0.020 0.000 0.004 0.096
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4684 5.46e-01 0.372 0.000 0.576 0.000 0.000 0.052
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2178 5.09e-01 0.000 0.868 0.000 0.000 0.132 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4806 -2.20e-01 0.560 0.000 0.380 0.000 0.000 0.060
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.3728 -6.00e-02 0.652 0.000 0.344 0.000 0.000 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.5579 4.40e-01 0.000 0.168 0.000 0.644 0.144 0.044
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 6 0.8112 -2.59e-01 0.096 0.288 0.044 0.004 0.248 0.320
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.6198 4.24e-01 0.248 0.000 0.484 0.000 0.016 0.252
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2450 6.68e-01 0.064 0.000 0.012 0.024 0.004 0.896
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0632 8.40e-01 0.000 0.024 0.000 0.976 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.5906 -1.08e-02 0.520 0.000 0.320 0.000 0.020 0.140
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4993 3.79e-01 0.608 0.000 0.044 0.000 0.024 0.324
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.3854 -3.45e-01 0.000 0.536 0.000 0.000 0.464 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.6561 5.31e-01 0.068 0.000 0.228 0.000 0.188 0.516
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 5 0.6706 1.83e-01 0.000 0.076 0.004 0.324 0.468 0.128
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.3189 2.91e-01 0.760 0.000 0.236 0.000 0.000 0.004
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.6491 -1.12e-01 0.332 0.000 0.324 0.000 0.016 0.328
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4581 4.28e-01 0.740 0.000 0.152 0.000 0.040 0.068
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.4654 3.10e-01 0.000 0.652 0.000 0.080 0.268 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.6039 2.43e-01 0.356 0.000 0.392 0.000 0.000 0.252
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0891 5.11e-01 0.968 0.000 0.008 0.000 0.000 0.024
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.1285 5.64e-01 0.000 0.944 0.000 0.004 0.052 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0858 4.98e-01 0.968 0.000 0.028 0.000 0.004 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.3317 5.93e-01 0.156 0.000 0.032 0.004 0.000 0.808
#> 311D089C-33F1-4722-9118-F56427C5C128 6 0.6207 5.63e-01 0.064 0.000 0.224 0.004 0.128 0.580
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.3864 -3.50e-01 0.000 0.520 0.000 0.000 0.480 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.5819 -1.02e-01 0.000 0.420 0.000 0.396 0.184 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.1908 4.50e-01 0.900 0.000 0.096 0.000 0.000 0.004
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.3196 4.97e-01 0.000 0.828 0.000 0.064 0.108 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3636 4.89e-01 0.772 0.000 0.016 0.000 0.016 0.196
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0790 5.68e-01 0.000 0.968 0.000 0.032 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 6 0.3872 6.34e-01 0.116 0.000 0.048 0.000 0.036 0.800
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.4683 3.94e-01 0.672 0.000 0.032 0.000 0.032 0.264
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6050 2.79e-01 0.516 0.000 0.144 0.000 0.028 0.312
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.4080 -3.37e-01 0.536 0.000 0.456 0.000 0.000 0.008
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.3578 3.37e-01 0.000 0.660 0.000 0.000 0.340 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 6 0.7806 3.93e-01 0.248 0.000 0.212 0.004 0.236 0.300
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.2972 5.05e-01 0.836 0.000 0.036 0.000 0.000 0.128
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.4840 2.24e-01 0.044 0.000 0.324 0.016 0.000 0.616
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.1444 5.58e-01 0.000 0.928 0.000 0.000 0.072 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.3930 3.47e-01 0.000 0.028 0.216 0.000 0.744 0.012
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2697 3.73e-01 0.000 0.812 0.000 0.000 0.188 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.2759 4.66e-01 0.880 0.000 0.064 0.008 0.040 0.008
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.2234 4.24e-01 0.872 0.000 0.124 0.000 0.000 0.004
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.5954 2.04e-01 0.016 0.644 0.172 0.000 0.072 0.096
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.4684 3.28e-01 0.656 0.000 0.256 0.000 0.000 0.088
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 1 0.4108 2.94e-01 0.708 0.000 0.260 0.004 0.016 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.5248 1.64e-01 0.536 0.000 0.040 0.000 0.032 0.392
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 6 0.5346 3.40e-01 0.356 0.000 0.036 0.000 0.048 0.560
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.3787 5.60e-01 0.260 0.000 0.720 0.000 0.012 0.008
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.3610 5.71e-01 0.052 0.000 0.000 0.152 0.004 0.792
#> 46351E5C-2438-4B6A-8343-DDF329086771 5 0.3868 3.84e-01 0.000 0.496 0.000 0.000 0.504 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.1938 6.56e-01 0.016 0.000 0.028 0.024 0.004 0.928
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.3795 5.62e-01 0.364 0.000 0.632 0.000 0.000 0.004
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.6173 3.76e-01 0.372 0.000 0.400 0.000 0.008 0.220
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 5 0.3868 3.83e-01 0.000 0.496 0.000 0.000 0.504 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.5027 -3.92e-01 0.488 0.000 0.448 0.000 0.004 0.060
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#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.3673 5.53e-01 0.244 0.000 0.736 0.000 0.016 0.004
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.3126 4.19e-01 0.000 0.752 0.000 0.000 0.248 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 5 0.3847 3.25e-01 0.000 0.456 0.000 0.000 0.544 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.3823 5.03e-01 0.436 0.000 0.564 0.000 0.000 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 5 0.7343 4.10e-01 0.040 0.296 0.044 0.004 0.440 0.176
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.4204 4.32e-01 0.000 0.772 0.004 0.128 0.080 0.016
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.5751 -2.26e-01 0.000 0.504 0.000 0.208 0.288 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.4912 4.58e-01 0.000 0.040 0.000 0.632 0.300 0.028
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.5723 -3.39e-01 0.000 0.460 0.116 0.000 0.412 0.012
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 6 0.2618 6.64e-01 0.092 0.000 0.024 0.004 0.004 0.876
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 6 0.2173 6.38e-01 0.000 0.000 0.064 0.028 0.004 0.904
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 6 0.5426 4.11e-01 0.324 0.000 0.044 0.000 0.052 0.580
#> B57C849C-28B1-4315-885C-330B9C9482B3 1 0.3368 3.20e-01 0.756 0.000 0.232 0.000 0.000 0.012
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4047 2.43e-01 0.000 0.676 0.000 0.296 0.028 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 5 0.2527 4.70e-01 0.000 0.168 0.000 0.000 0.832 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
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#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.6162 2.67e-01 0.272 0.000 0.548 0.000 0.056 0.124
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4012 4.41e-01 0.716 0.000 0.016 0.000 0.016 0.252
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 6 0.5770 5.28e-01 0.028 0.000 0.228 0.000 0.152 0.592
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.4205 3.49e-01 0.744 0.000 0.184 0.000 0.012 0.060
#> 17CA5D73-4384-4645-83F8-587847043DD2 6 0.2588 6.64e-01 0.092 0.000 0.024 0.008 0.000 0.876
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.4554 3.16e-01 0.640 0.000 0.028 0.000 0.016 0.316
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 6 0.5399 3.93e-01 0.316 0.000 0.052 0.000 0.044 0.588
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 6 0.4585 5.34e-01 0.156 0.000 0.076 0.000 0.032 0.736
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.4192 5.25e-01 0.412 0.000 0.572 0.000 0.000 0.016
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.3841 5.52e-01 0.380 0.000 0.616 0.000 0.000 0.004
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 6 0.7957 8.19e-02 0.052 0.236 0.136 0.004 0.140 0.432
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 6 0.5830 4.68e-01 0.008 0.000 0.344 0.000 0.156 0.492
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.3869 -3.99e-01 0.000 0.500 0.000 0.000 0.500 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 6 0.1563 6.66e-01 0.056 0.000 0.012 0.000 0.000 0.932
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.3435 4.53e-01 0.804 0.000 0.136 0.000 0.000 0.060
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#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.7831 2.03e-01 0.224 0.068 0.412 0.000 0.068 0.228
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 6 0.4139 4.19e-01 0.336 0.000 0.024 0.000 0.000 0.640
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 5 0.5159 4.66e-01 0.000 0.380 0.000 0.092 0.528 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 6 0.5436 2.26e-01 0.000 0.012 0.040 0.316 0.036 0.596
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.5363 -3.08e-01 0.000 0.496 0.096 0.000 0.404 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 6 0.4378 3.08e-01 0.388 0.000 0.008 0.000 0.016 0.588
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 5 0.5828 4.95e-01 0.000 0.332 0.044 0.000 0.540 0.084
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.3945 -1.72e-01 0.612 0.000 0.380 0.000 0.000 0.008
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3309 5.75e-01 0.280 0.000 0.720 0.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 6 0.5527 5.01e-01 0.004 0.000 0.300 0.000 0.144 0.552
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.3868 -3.94e-01 0.000 0.504 0.000 0.000 0.496 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4406 3.16e-01 0.624 0.000 0.024 0.000 0.008 0.344
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4703 4.62e-01 0.684 0.000 0.064 0.000 0.016 0.236
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0260 5.77e-01 0.000 0.992 0.000 0.000 0.008 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.5449 -4.18e-02 0.000 0.500 0.000 0.388 0.108 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.5891 -9.92e-02 0.468 0.000 0.300 0.000 0.000 0.232
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.4705 4.27e-01 0.472 0.000 0.484 0.000 0.000 0.044
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 3 0.5447 3.63e-01 0.420 0.000 0.460 0.000 0.000 0.120
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.0935 6.60e-01 0.004 0.000 0.032 0.000 0.000 0.964
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.1910 4.96e-01 0.000 0.892 0.000 0.000 0.108 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0937 5.70e-01 0.000 0.960 0.000 0.000 0.040 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4246 4.78e-01 0.452 0.000 0.532 0.000 0.000 0.016
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 6 0.5148 5.18e-01 0.240 0.000 0.100 0.000 0.016 0.644
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4478 -1.70e-01 0.532 0.000 0.444 0.000 0.012 0.012
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.3592 5.71e-01 0.344 0.000 0.656 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.5510 1.13e-01 0.424 0.000 0.488 0.000 0.036 0.052
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.3982 -3.57e-01 0.536 0.000 0.460 0.000 0.000 0.004
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.3136 5.54e-01 0.228 0.000 0.768 0.000 0.000 0.004
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4168 2.99e-01 0.696 0.000 0.256 0.000 0.000 0.048
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.2712 5.16e-01 0.864 0.000 0.016 0.000 0.012 0.108
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.4789 4.08e-01 0.692 0.000 0.124 0.000 0.008 0.176
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 5 0.4078 5.12e-01 0.000 0.340 0.000 0.020 0.640 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.5332 4.13e-01 0.168 0.000 0.628 0.004 0.004 0.196
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4570 8.42e-02 0.644 0.000 0.308 0.000 0.012 0.036
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 1 0.6648 1.51e-01 0.552 0.004 0.172 0.004 0.188 0.080
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4345 2.90e-01 0.628 0.000 0.012 0.000 0.016 0.344
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.2697 4.78e-01 0.000 0.812 0.000 0.000 0.188 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.3774 -2.16e-01 0.000 0.592 0.000 0.000 0.408 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.2628 6.68e-01 0.068 0.000 0.024 0.024 0.000 0.884
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1434 5.13e-01 0.948 0.000 0.012 0.000 0.012 0.028
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.3996 -3.72e-01 0.512 0.000 0.484 0.000 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.2745 6.37e-01 0.068 0.000 0.068 0.000 0.000 0.864
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.4241 -1.07e-01 0.608 0.000 0.368 0.000 0.000 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 5 0.6100 1.71e-01 0.000 0.284 0.000 0.356 0.360 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0632 8.29e-01 0.000 0.000 0.000 0.976 0.000 0.024
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.2007 6.64e-01 0.036 0.000 0.032 0.012 0.000 0.920
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.5993 2.44e-01 0.000 0.288 0.000 0.272 0.440 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.1863 6.61e-01 0.044 0.000 0.036 0.000 0.000 0.920
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.4604 2.24e-01 0.432 0.000 0.024 0.000 0.008 0.536
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3864 4.39e-01 0.480 0.000 0.520 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.5982 3.60e-01 0.596 0.000 0.220 0.000 0.064 0.120
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.3899 -2.10e-01 0.592 0.000 0.404 0.000 0.000 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.4015 3.46e-01 0.000 0.372 0.000 0.616 0.012 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.1285 5.58e-01 0.000 0.944 0.000 0.004 0.052 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 5 0.6648 3.47e-01 0.052 0.356 0.136 0.000 0.448 0.008
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.5668 -1.47e-01 0.100 0.000 0.408 0.000 0.016 0.476
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.5323 3.01e-01 0.272 0.000 0.120 0.000 0.008 0.600
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.5748 -1.44e-01 0.464 0.000 0.360 0.000 0.000 0.176
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.2805 3.80e-01 0.828 0.000 0.160 0.000 0.000 0.012
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5966 3.60e-01 0.576 0.000 0.164 0.000 0.036 0.224
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5559 -1.62e-01 0.000 0.540 0.000 0.176 0.284 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.1490 6.53e-01 0.008 0.000 0.016 0.024 0.004 0.948
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 4 0.6039 -2.30e-01 0.000 0.356 0.000 0.392 0.252 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4206 -1.11e-01 0.620 0.000 0.356 0.000 0.000 0.024
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2711 5.16e-01 0.860 0.000 0.012 0.000 0.012 0.116
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.5024 2.04e-01 0.408 0.000 0.536 0.000 0.028 0.028
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0260 5.00e-01 0.992 0.000 0.008 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.5789 1.96e-02 0.000 0.496 0.000 0.288 0.216 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.5646 -1.16e-01 0.500 0.000 0.356 0.000 0.004 0.140
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5479 -1.45e-01 0.500 0.000 0.368 0.000 0.000 0.132
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.5798 3.57e-01 0.396 0.000 0.456 0.000 0.008 0.140
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4436 3.51e-01 0.652 0.000 0.028 0.000 0.012 0.308
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0260 8.51e-01 0.000 0.008 0.000 0.992 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4246 4.33e-01 0.692 0.000 0.028 0.000 0.012 0.268
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.3371 4.05e-01 0.008 0.796 0.180 0.000 0.012 0.004
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.7112 1.79e-01 0.328 0.196 0.416 0.008 0.036 0.016
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 5.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5172 3.65e-01 0.660 0.000 0.116 0.000 0.020 0.204
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.5337 5.16e-01 0.236 0.000 0.060 0.004 0.048 0.652
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.5491 5.14e-01 0.332 0.000 0.524 0.000 0.000 0.144
#> 2785594A-571A-46B4-A901-CB9C62DC6174 6 0.4433 2.39e-01 0.416 0.000 0.008 0.000 0.016 0.560
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.797 0.881 0.951 0.4983 0.502 0.502
#> 3 3 0.528 0.716 0.852 0.3294 0.711 0.485
#> 4 4 0.511 0.506 0.705 0.1029 0.773 0.470
#> 5 5 0.709 0.703 0.858 0.0681 0.842 0.533
#> 6 6 0.734 0.667 0.809 0.0431 0.925 0.692
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 2 0.0000 0.94890 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.94406 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0000 0.94890 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.0000 0.94406 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.1633 0.92800 0.976 0.024
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.94890 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.9686 0.36511 0.396 0.604
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.6438 0.79874 0.836 0.164
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.0000 0.94890 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 2 0.0000 0.94890 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0000 0.94890 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.8909 0.58116 0.692 0.308
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.5519 0.82914 0.128 0.872
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.4161 0.87929 0.084 0.916
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.94406 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.0000 0.94890 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0000 0.94406 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0672 0.94327 0.008 0.992
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.9954 0.17124 0.460 0.540
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.94890 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.0000 0.94890 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.94890 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.94406 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.94890 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.94406 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.94890 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.0376 0.94612 0.004 0.996
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.94406 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.2043 0.92362 0.968 0.032
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.6247 0.80793 0.844 0.156
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.9710 0.37184 0.600 0.400
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.94890 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.0000 0.94406 1.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.8909 0.58119 0.692 0.308
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.0000 0.94890 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.0000 0.94406 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.0000 0.94406 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.94406 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.94406 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.0000 0.94406 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.7219 0.75356 0.800 0.200
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0672 0.93955 0.992 0.008
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.94890 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.94406 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0000 0.94406 1.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.0000 0.94890 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.94890 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.94406 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 2 0.0000 0.94890 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.6887 0.75998 0.184 0.816
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.94406 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.9248 0.51606 0.660 0.340
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.0938 0.94039 0.012 0.988
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.0000 0.94890 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.94406 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.94406 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.94890 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.0000 0.94406 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0000 0.94890 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.9522 0.42224 0.372 0.628
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.94406 1.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.6531 0.78088 0.168 0.832
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.94406 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.94406 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 2 0.7674 0.70286 0.224 0.776
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 2 0.0000 0.94890 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 2 0.0000 0.94890 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.94406 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.94406 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.94406 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0376 0.94609 0.004 0.996
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 2 0.0000 0.94890 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.94890 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.94890 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0000 0.94890 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.0000 0.94406 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.0000 0.94890 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0000 0.94890 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.3584 0.89539 0.932 0.068
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.94890 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.94406 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.94890 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.94406 1.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.0000 0.94890 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.94406 1.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.94890 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.94406 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.0000 0.94890 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.94406 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.94890 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.94406 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.8267 0.62642 0.260 0.740
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0000 0.94406 1.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0672 0.94326 0.008 0.992
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0938 0.93710 0.988 0.012
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 2 0.0000 0.94890 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.9522 0.42226 0.372 0.628
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.94890 0.000 1.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 1 0.0000 0.94406 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.94890 0.000 1.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.94406 1.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.0000 0.94406 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0000 0.94890 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.94890 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.0000 0.94406 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 2 0.0000 0.94890 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 1 0.0672 0.93948 0.992 0.008
#> AE903797-7FFB-44A1-B834-C644784B5DC2 2 0.7453 0.70871 0.212 0.788
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.94890 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.94406 1.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.0000 0.94406 1.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.0672 0.93918 0.992 0.008
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.3114 0.90386 0.056 0.944
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 2 0.3114 0.90217 0.056 0.944
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.0000 0.94406 1.000 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.94890 0.000 1.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 2 0.0000 0.94890 0.000 1.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.94890 0.000 1.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 2 0.0000 0.94890 0.000 1.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.94406 1.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.0000 0.94406 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 1 0.0000 0.94406 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 1 0.9460 0.41460 0.636 0.364
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 2 0.0000 0.94890 0.000 1.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.0000 0.94890 0.000 1.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.0000 0.94406 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.0000 0.94406 1.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 2 0.0000 0.94890 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 1 0.0000 0.94406 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 2 0.4161 0.87686 0.084 0.916
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.8144 0.67843 0.748 0.252
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.94890 0.000 1.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 2 0.0000 0.94890 0.000 1.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 2 0.0938 0.93998 0.012 0.988
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.0000 0.94406 1.000 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 2 0.0000 0.94890 0.000 1.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 1 0.0000 0.94406 1.000 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.94890 0.000 1.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 1 0.0000 0.94406 1.000 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.94890 0.000 1.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 2 0.0000 0.94890 0.000 1.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 2 0.0000 0.94890 0.000 1.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.94890 0.000 1.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.94890 0.000 1.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 1 0.0000 0.94406 1.000 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.94890 0.000 1.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.94890 0.000 1.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0000 0.94406 1.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 2 0.0000 0.94890 0.000 1.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 1 0.0000 0.94406 1.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.94890 0.000 1.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 2 0.0000 0.94890 0.000 1.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 2 0.0000 0.94890 0.000 1.000
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#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 1 0.0000 0.94406 1.000 0.000
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 2 0.0000 0.94890 0.000 1.000
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 2 0.0000 0.94890 0.000 1.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.0000 0.94406 1.000 0.000
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 2 0.0000 0.94890 0.000 1.000
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 2 0.3114 0.90509 0.056 0.944
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.0000 0.94890 0.000 1.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 1 0.4690 0.86609 0.900 0.100
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.94890 0.000 1.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.94890 0.000 1.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0000 0.94890 0.000 1.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 2 0.0000 0.94890 0.000 1.000
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.94890 0.000 1.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.0000 0.94406 1.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 2 0.0000 0.94890 0.000 1.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 2 0.0000 0.94890 0.000 1.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 2 0.0000 0.94890 0.000 1.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.0000 0.94406 1.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.94890 0.000 1.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.94890 0.000 1.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.0000 0.94406 1.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.2423 0.91785 0.040 0.960
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.0000 0.94890 0.000 1.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0000 0.94406 1.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.94890 0.000 1.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.0000 0.94406 1.000 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 2 0.3879 0.88282 0.076 0.924
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0000 0.94406 1.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.3879 0.88473 0.076 0.924
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.9460 0.45902 0.636 0.364
#> 34ED910C-7470-4552-8561-D01D59190521 2 0.0000 0.94890 0.000 1.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.0000 0.94890 0.000 1.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.0000 0.94406 1.000 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.0000 0.94890 0.000 1.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.94890 0.000 1.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 2 0.0000 0.94890 0.000 1.000
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.3879 0.88423 0.924 0.076
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 1 0.8016 0.66682 0.756 0.244
#> E789661A-C027-405D-9F76-E6D52CE3018B 1 0.9922 0.16500 0.552 0.448
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.0000 0.94406 1.000 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0000 0.94890 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.94406 1.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.94406 1.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.1843 0.92678 0.972 0.028
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.94406 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.0000 0.94890 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 1 0.5294 0.83936 0.880 0.120
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.0000 0.94890 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.94890 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.94890 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.94406 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0376 0.94612 0.004 0.996
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.94406 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.94406 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.94890 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.7602 0.72625 0.780 0.220
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.94406 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.94406 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0000 0.94406 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.94406 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 2 0.0000 0.94890 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 2 0.0000 0.94890 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0000 0.94406 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.0000 0.94406 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.94406 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.94890 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0000 0.94406 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.8499 0.63901 0.724 0.276
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.0000 0.94890 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0000 0.94406 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1633 0.92939 0.976 0.024
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0376 0.94612 0.004 0.996
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.94406 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.0000 0.94406 1.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.0000 0.94406 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.94890 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.2603 0.91451 0.044 0.956
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.94406 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.0000 0.94890 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.0000 0.94890 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.0000 0.94890 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.94406 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.94890 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.94406 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.94406 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.9686 0.38481 0.604 0.396
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.94890 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 1 0.2043 0.92210 0.968 0.032
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.94406 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.9881 0.26824 0.564 0.436
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.94406 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.94406 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.94890 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.94890 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.94406 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.6148 0.79464 0.152 0.848
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.94406 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.0000 0.94890 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.0000 0.94890 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.9922 0.15009 0.448 0.552
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.0000 0.94890 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.94890 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4431 0.87386 0.908 0.092
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.5629 0.83417 0.868 0.132
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0376 0.94186 0.996 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.6048 0.80627 0.852 0.148
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.6801 0.76530 0.180 0.820
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.1414 0.93362 0.020 0.980
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.94890 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.94406 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.94890 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.94890 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.94406 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.9996 -0.00146 0.488 0.512
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.0000 0.94890 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.94406 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.8081 0.68488 0.752 0.248
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.4690 0.86041 0.900 0.100
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.94406 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.94406 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.94406 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.9460 0.41493 0.636 0.364
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.94406 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.94406 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.0000 0.94890 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.94406 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.8861 0.58905 0.696 0.304
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.0000 0.94890 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9963 0.15752 0.464 0.536
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.9286 0.48727 0.344 0.656
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.94890 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.94406 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0672 0.93921 0.992 0.008
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.94406 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.94406 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.0000 0.94890 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.94406 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.9286 0.48655 0.344 0.656
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.94406 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.8661 0.58562 0.712 0.288
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.9996 -0.00208 0.488 0.512
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.7139 0.75887 0.804 0.196
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.0000 0.94890 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0000 0.94890 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.9850 0.27302 0.428 0.572
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.94406 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2043 0.92379 0.968 0.032
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.94406 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.94406 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.94406 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.94406 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.94890 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.0000 0.94890 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.94890 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0938 0.93710 0.988 0.012
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0376 0.94188 0.996 0.004
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.94406 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.94406 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 3 0.5327 0.57635 0.000 0.272 0.728
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.4504 0.70680 0.196 0.804 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0424 0.79746 0.000 0.008 0.992
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.5016 0.65063 0.240 0.760 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1031 0.80072 0.024 0.976 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.3192 0.77575 0.112 0.000 0.888
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.1647 0.80789 0.004 0.960 0.036
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2537 0.86620 0.920 0.000 0.080
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0592 0.80119 0.012 0.000 0.988
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.0892 0.80102 0.020 0.000 0.980
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.5650 0.57222 0.000 0.688 0.312
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4702 0.74636 0.788 0.000 0.212
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0892 0.80681 0.000 0.980 0.020
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.8967 0.14439 0.488 0.132 0.380
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.5291 0.61085 0.268 0.732 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.4002 0.73353 0.160 0.000 0.840
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.5678 0.53451 0.316 0.684 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.2625 0.79947 0.000 0.916 0.084
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0661 0.80461 0.008 0.988 0.004
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.6260 0.24474 0.000 0.552 0.448
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.3482 0.72505 0.000 0.128 0.872
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2356 0.80225 0.000 0.928 0.072
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0892 0.86822 0.980 0.020 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5529 0.59830 0.000 0.704 0.296
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.3482 0.77905 0.872 0.128 0.000
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#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.6140 0.38993 0.596 0.000 0.404
#> 34ED910C-7470-4552-8561-D01D59190521 3 0.7829 0.66867 0.164 0.164 0.672
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.1031 0.79196 0.000 0.024 0.976
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.3551 0.75618 0.132 0.868 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 2 0.3752 0.77103 0.000 0.856 0.144
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.3482 0.78085 0.000 0.872 0.128
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.2356 0.79375 0.072 0.000 0.928
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.1999 0.80368 0.036 0.952 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.1163 0.80271 0.028 0.972 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.0424 0.80422 0.008 0.992 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 2 0.5650 0.54175 0.312 0.688 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.3267 0.74105 0.000 0.116 0.884
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0237 0.87464 0.996 0.004 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.2959 0.80768 0.900 0.100 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.2165 0.87399 0.936 0.000 0.064
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0592 0.87190 0.988 0.012 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0237 0.80000 0.004 0.000 0.996
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.3941 0.73619 0.156 0.844 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.6309 0.07455 0.000 0.504 0.496
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 3 0.6307 -0.11544 0.000 0.488 0.512
#> 80936433-AA91-4219-98F1-706C36298060 2 0.3038 0.79236 0.000 0.896 0.104
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 2 0.5363 0.60169 0.276 0.724 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.8982 0.47644 0.284 0.168 0.548
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.1643 0.87915 0.956 0.000 0.044
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0747 0.87006 0.984 0.016 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.4842 0.60927 0.000 0.224 0.776
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.3816 0.81719 0.852 0.000 0.148
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0592 0.87179 0.988 0.012 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0892 0.87950 0.980 0.000 0.020
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0237 0.87464 0.996 0.004 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0747 0.87887 0.984 0.000 0.016
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.2711 0.78854 0.088 0.000 0.912
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.2796 0.78653 0.092 0.000 0.908
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 2 0.4974 0.65630 0.236 0.764 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.6267 0.18176 0.548 0.452 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0237 0.87464 0.996 0.004 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4887 0.69358 0.000 0.772 0.228
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.2165 0.83893 0.936 0.064 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.4702 0.75148 0.788 0.000 0.212
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.4002 0.73327 0.160 0.000 0.840
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.2356 0.83265 0.928 0.072 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.2356 0.87043 0.928 0.000 0.072
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.9243 0.49774 0.232 0.236 0.532
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.87576 1.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.1411 0.79739 0.036 0.964 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.6252 0.14127 0.556 0.444 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.2959 0.74776 0.000 0.100 0.900
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.1163 0.80717 0.000 0.972 0.028
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0237 0.87464 0.996 0.004 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.5678 0.56673 0.000 0.684 0.316
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.3412 0.76637 0.124 0.000 0.876
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.79929 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.1964 0.84501 0.944 0.056 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.2878 0.79547 0.000 0.904 0.096
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.5016 0.65121 0.240 0.760 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.1031 0.87980 0.976 0.000 0.024
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4796 0.73904 0.780 0.000 0.220
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 3 0.5678 0.49626 0.000 0.316 0.684
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.1163 0.79965 0.028 0.972 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.1289 0.88009 0.968 0.000 0.032
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.6308 -0.05845 0.492 0.000 0.508
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.4121 0.79863 0.832 0.000 0.168
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.1964 0.84516 0.944 0.056 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.3619 0.77603 0.000 0.864 0.136
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.6305 0.12166 0.000 0.516 0.484
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.3619 0.75412 0.136 0.864 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4974 0.63842 0.236 0.000 0.764
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.1163 0.86479 0.972 0.028 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.2959 0.78309 0.100 0.000 0.900
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1753 0.79956 0.048 0.000 0.952
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.8126 0.35354 0.564 0.080 0.356
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.1163 0.80080 0.028 0.000 0.972
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0892 0.79371 0.000 0.020 0.980
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4235 0.79176 0.824 0.000 0.176
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.2625 0.86404 0.916 0.000 0.084
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.2165 0.87373 0.936 0.000 0.064
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1031 0.80072 0.024 0.976 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.5988 0.33807 0.000 0.368 0.632
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.6849 0.35416 0.380 0.020 0.600
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.1163 0.79000 0.000 0.028 0.972
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0892 0.87950 0.980 0.000 0.020
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.3340 0.78535 0.000 0.880 0.120
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.3619 0.77629 0.000 0.864 0.136
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1163 0.86367 0.972 0.028 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.5988 0.46706 0.632 0.000 0.368
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.3412 0.76621 0.124 0.000 0.876
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0237 0.87464 0.996 0.004 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.3879 0.81386 0.848 0.000 0.152
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.0892 0.80151 0.020 0.980 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.6267 0.11703 0.548 0.452 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.6126 0.35449 0.400 0.600 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0424 0.87336 0.992 0.008 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.1129 0.80269 0.020 0.976 0.004
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0747 0.87006 0.984 0.016 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.1289 0.88009 0.968 0.000 0.032
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.3752 0.74889 0.144 0.000 0.856
#> 1122039D-5785-4F70-9916-17C585453512 2 0.4654 0.68698 0.208 0.792 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.6224 0.68092 0.728 0.032 0.240
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.3267 0.77255 0.116 0.000 0.884
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.0000 0.80492 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0424 0.80586 0.000 0.992 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.6274 -0.00811 0.000 0.456 0.544
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0424 0.87336 0.992 0.008 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.3879 0.74264 0.152 0.848 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0892 0.87950 0.980 0.000 0.020
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1753 0.87858 0.952 0.000 0.048
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0747 0.80102 0.016 0.000 0.984
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0424 0.87795 0.992 0.000 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0424 0.80586 0.000 0.992 0.008
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2448 0.82934 0.924 0.076 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0983 0.80338 0.016 0.980 0.004
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.6192 0.21388 0.420 0.000 0.580
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2796 0.85980 0.908 0.000 0.092
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.6332 0.74107 0.144 0.088 0.768
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.2356 0.79383 0.072 0.000 0.928
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0424 0.80586 0.000 0.992 0.008
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1753 0.87858 0.952 0.000 0.048
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2448 0.86826 0.924 0.000 0.076
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.1860 0.87770 0.948 0.000 0.052
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1411 0.87997 0.964 0.000 0.036
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.2878 0.77560 0.096 0.904 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1163 0.88013 0.972 0.000 0.028
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.2356 0.76613 0.000 0.072 0.928
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1163 0.79000 0.000 0.028 0.972
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.5216 0.65165 0.000 0.740 0.260
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2165 0.87375 0.936 0.000 0.064
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5292 0.65798 0.764 0.228 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.2165 0.87450 0.936 0.000 0.064
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.87576 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 3 0.8265 0.118834 0.016 0.360 0.380 0.244
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.5414 0.600729 0.020 0.376 0.000 0.604
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.5711 0.682921 0.012 0.028 0.656 0.304
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.5467 0.608698 0.024 0.364 0.000 0.612
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3400 0.530860 0.000 0.820 0.000 0.180
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.7283 0.375721 0.556 0.016 0.120 0.308
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4262 0.602716 0.008 0.756 0.000 0.236
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0804 0.720068 0.980 0.000 0.008 0.012
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.3862 0.663809 0.060 0.004 0.852 0.084
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.3455 0.545179 0.044 0.012 0.880 0.064
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.6743 0.308044 0.004 0.504 0.412 0.080
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3088 0.707897 0.864 0.000 0.008 0.128
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.3942 0.444131 0.000 0.764 0.000 0.236
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.8019 0.313988 0.480 0.072 0.368 0.080
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.6637 0.616548 0.132 0.260 0.000 0.608
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5859 0.527882 0.652 0.000 0.064 0.284
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.5920 0.616384 0.052 0.336 0.000 0.612
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4953 0.552072 0.000 0.776 0.104 0.120
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.2011 0.622667 0.000 0.920 0.000 0.080
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.5161 0.512121 0.000 0.676 0.300 0.024
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.6308 0.651344 0.000 0.120 0.648 0.232
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1792 0.631207 0.000 0.932 0.000 0.068
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2345 0.675261 0.900 0.000 0.000 0.100
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.1929 0.660192 0.000 0.940 0.024 0.036
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.5628 0.337137 0.420 0.024 0.000 0.556
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 3 0.2081 0.587390 0.000 0.084 0.916 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.7042 0.421616 0.580 0.036 0.064 0.320
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2011 0.688918 0.920 0.000 0.000 0.080
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.3751 0.675419 0.800 0.004 0.000 0.196
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2081 0.719491 0.916 0.000 0.000 0.084
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.4103 0.627413 0.744 0.000 0.256 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4663 0.559348 0.000 0.716 0.272 0.012
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 4 0.5050 0.567922 0.004 0.408 0.000 0.588
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4837 0.514634 0.648 0.000 0.348 0.004
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.6752 0.454582 0.588 0.000 0.280 0.132
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.6701 0.598435 0.108 0.328 0.000 0.564
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.5662 0.383627 0.236 0.692 0.000 0.072
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.4720 0.385111 0.672 0.000 0.004 0.324
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#> E71AD72B-D55B-4654-89F7-C31CA32624F4 3 0.1716 0.581336 0.000 0.064 0.936 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.4304 0.457405 0.716 0.000 0.000 0.284
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.3621 0.638332 0.000 0.860 0.068 0.072
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.7603 0.634560 0.116 0.032 0.544 0.308
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.4898 0.145865 0.584 0.000 0.000 0.416
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.4538 0.455321 0.000 0.760 0.024 0.216
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.1004 0.712436 0.972 0.000 0.004 0.024
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 1 0.6833 0.428538 0.584 0.000 0.144 0.272
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.1022 0.710240 0.968 0.000 0.000 0.032
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.1488 0.644117 0.000 0.956 0.012 0.032
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.4999 -0.266669 0.492 0.000 0.508 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.8633 0.309213 0.484 0.144 0.288 0.084
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.5310 0.690840 0.008 0.028 0.704 0.260
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 4 0.4898 0.556385 0.000 0.416 0.000 0.584
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 3 0.6610 -0.225335 0.000 0.452 0.468 0.080
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0592 0.657931 0.000 0.984 0.000 0.016
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.2908 0.642999 0.064 0.000 0.896 0.040
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.2861 0.636185 0.016 0.888 0.000 0.096
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.4817 0.012962 0.000 0.612 0.000 0.388
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.4679 0.139219 0.000 0.648 0.000 0.352
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 4 0.5937 0.417781 0.036 0.472 0.000 0.492
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.7977 -0.132935 0.004 0.412 0.280 0.304
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.1867 0.694491 0.928 0.000 0.000 0.072
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.5244 0.300629 0.436 0.008 0.000 0.556
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.1388 0.713202 0.960 0.000 0.012 0.028
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.1452 0.718812 0.956 0.008 0.000 0.036
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.6370 0.675523 0.040 0.028 0.628 0.304
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 4 0.4992 0.428803 0.000 0.476 0.000 0.524
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 2 0.5186 0.446689 0.016 0.640 0.000 0.344
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.5487 0.281395 0.000 0.580 0.400 0.020
#> 80936433-AA91-4219-98F1-706C36298060 2 0.4095 0.524391 0.000 0.804 0.024 0.172
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.5973 0.617002 0.056 0.332 0.000 0.612
#> 241F589C-D559-43D7-8340-31EBCEB36E14 1 0.9131 0.094030 0.364 0.212 0.344 0.080
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0336 0.717958 0.992 0.000 0.000 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.2921 0.646174 0.860 0.000 0.000 0.140
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.6592 0.467202 0.000 0.284 0.600 0.116
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.2198 0.718760 0.920 0.000 0.008 0.072
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.1557 0.701690 0.944 0.000 0.000 0.056
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.1557 0.720818 0.944 0.000 0.000 0.056
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.0921 0.716319 0.972 0.000 0.000 0.028
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.2081 0.688211 0.916 0.000 0.000 0.084
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0592 0.613056 0.016 0.000 0.984 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.5935 0.679600 0.080 0.000 0.664 0.256
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.5112 0.594566 0.008 0.384 0.000 0.608
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.7516 0.101161 0.328 0.472 0.000 0.200
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.3975 0.569886 0.760 0.000 0.000 0.240
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4454 0.476724 0.000 0.692 0.000 0.308
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.4761 0.270319 0.628 0.000 0.000 0.372
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.3247 0.712873 0.880 0.000 0.060 0.060
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.6544 0.452525 0.604 0.000 0.112 0.284
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.4718 0.454085 0.708 0.012 0.000 0.280
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1743 0.714028 0.940 0.000 0.004 0.056
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.9294 0.004795 0.308 0.288 0.324 0.080
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.1867 0.695033 0.928 0.000 0.000 0.072
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.1902 0.633931 0.004 0.932 0.000 0.064
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.6691 0.592739 0.236 0.152 0.000 0.612
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.7912 0.459193 0.004 0.260 0.432 0.304
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.4585 0.203545 0.000 0.668 0.000 0.332
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0817 0.713933 0.976 0.000 0.000 0.024
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.6963 0.308046 0.004 0.560 0.120 0.316
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.6852 0.449619 0.600 0.000 0.192 0.208
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.5195 0.693387 0.028 0.016 0.740 0.216
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.6542 0.142064 0.428 0.076 0.000 0.496
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.1557 0.660410 0.000 0.944 0.000 0.056
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.5467 0.608293 0.024 0.364 0.000 0.612
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0817 0.713229 0.976 0.000 0.000 0.024
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.3856 0.686252 0.832 0.000 0.032 0.136
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 3 0.4428 0.278622 0.000 0.276 0.720 0.004
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4888 -0.083885 0.000 0.588 0.000 0.412
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.1902 0.699787 0.932 0.000 0.004 0.064
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.4888 0.462003 0.588 0.000 0.412 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.4499 0.676801 0.804 0.000 0.124 0.072
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.4925 0.108304 0.572 0.000 0.000 0.428
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.2376 0.635591 0.000 0.916 0.016 0.068
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.4098 0.599650 0.000 0.784 0.204 0.012
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.5028 0.579339 0.004 0.400 0.000 0.596
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.5786 0.511580 0.640 0.000 0.308 0.052
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.4382 0.436947 0.704 0.000 0.000 0.296
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.8341 0.311223 0.484 0.092 0.332 0.092
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1284 0.624766 0.024 0.000 0.964 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.7158 0.495461 0.608 0.040 0.268 0.084
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0707 0.611054 0.020 0.000 0.980 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4963 0.691341 0.008 0.024 0.740 0.228
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.2816 0.717308 0.900 0.000 0.064 0.036
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.1474 0.720759 0.948 0.000 0.000 0.052
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0524 0.716556 0.988 0.000 0.004 0.008
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.1302 0.645324 0.000 0.956 0.000 0.044
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.7686 0.157536 0.004 0.312 0.476 0.208
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3791 0.704102 0.844 0.012 0.016 0.128
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.6968 0.659020 0.032 0.068 0.592 0.308
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.1302 0.720100 0.956 0.000 0.000 0.044
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.5708 0.371992 0.000 0.556 0.416 0.028
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.4415 0.616337 0.000 0.804 0.056 0.140
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.3356 0.613071 0.824 0.000 0.000 0.176
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.4607 0.599740 0.716 0.004 0.004 0.276
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.7110 0.397117 0.564 0.000 0.200 0.236
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2760 0.657161 0.872 0.000 0.000 0.128
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.1936 0.720846 0.940 0.000 0.032 0.028
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 2 0.2976 0.631396 0.008 0.872 0.000 0.120
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.6714 0.595647 0.228 0.160 0.000 0.612
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.6678 0.616785 0.148 0.240 0.000 0.612
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3610 0.584896 0.800 0.000 0.000 0.200
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.2469 0.637362 0.000 0.892 0.000 0.108
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.3400 0.607155 0.820 0.000 0.000 0.180
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.2530 0.673368 0.888 0.000 0.000 0.112
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.4933 -0.127940 0.432 0.000 0.568 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.4866 0.574250 0.000 0.404 0.000 0.596
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.4309 0.693286 0.820 0.040 0.008 0.132
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.6846 0.306376 0.484 0.012 0.436 0.068
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.4996 0.409777 0.000 0.484 0.000 0.516
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.4677 0.210972 0.000 0.680 0.004 0.316
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.7901 0.347444 0.000 0.316 0.372 0.312
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4843 0.203514 0.604 0.000 0.000 0.396
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.4866 0.574816 0.000 0.404 0.000 0.596
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.3123 0.633991 0.844 0.000 0.000 0.156
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1151 0.712463 0.968 0.000 0.008 0.024
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.6925 0.662868 0.072 0.028 0.596 0.304
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5492 0.519730 0.640 0.032 0.000 0.328
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2589 0.594914 0.000 0.884 0.000 0.116
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.5165 0.173188 0.484 0.004 0.000 0.512
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.1867 0.638369 0.000 0.928 0.000 0.072
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4411 0.675562 0.812 0.000 0.108 0.080
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2197 0.719580 0.916 0.000 0.004 0.080
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.8562 0.225652 0.432 0.120 0.368 0.080
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.8180 0.183012 0.472 0.028 0.192 0.308
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3266 0.540956 0.000 0.832 0.000 0.168
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1938 0.716020 0.936 0.000 0.012 0.052
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3229 0.713990 0.880 0.000 0.048 0.072
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.4562 0.627221 0.792 0.000 0.056 0.152
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0469 0.716584 0.988 0.000 0.000 0.012
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.5150 0.583924 0.008 0.396 0.000 0.596
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0817 0.714858 0.976 0.000 0.000 0.024
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4966 0.609978 0.000 0.156 0.768 0.076
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.5496 0.686794 0.008 0.028 0.676 0.288
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.1109 0.653444 0.000 0.968 0.004 0.028
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2737 0.712054 0.888 0.008 0.000 0.104
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.6433 0.356779 0.648 0.188 0.000 0.164
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.5127 0.307316 0.632 0.000 0.012 0.356
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0707 0.714883 0.980 0.000 0.000 0.020
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.5880 0.0979 0.000 0.100 0.416 0.000 0.484
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0290 0.8186 0.000 0.008 0.000 0.992 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8247 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.0162 0.8197 0.000 0.004 0.000 0.996 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1205 0.8675 0.000 0.956 0.000 0.040 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.1444 0.8304 0.948 0.012 0.040 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.2378 0.8370 0.048 0.904 0.048 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0162 0.8465 0.996 0.000 0.000 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0404 0.8204 0.000 0.000 0.988 0.000 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.0162 0.7254 0.004 0.000 0.000 0.000 0.996
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.1121 0.7245 0.000 0.044 0.000 0.000 0.956
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.8468 1.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.4334 0.7243 0.000 0.764 0.000 0.080 0.156
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.3562 0.6486 0.196 0.016 0.000 0.000 0.788
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0609 0.8117 0.000 0.020 0.000 0.980 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.8468 1.000 0.000 0.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0290 0.8187 0.000 0.008 0.000 0.992 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.3530 0.6118 0.000 0.204 0.000 0.012 0.784
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#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0566 0.8713 0.000 0.984 0.000 0.004 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0162 0.8467 0.996 0.000 0.004 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.8468 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.0880 0.7268 0.032 0.000 0.000 0.000 0.968
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.4003 0.5420 0.704 0.008 0.288 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.1282 0.8661 0.000 0.952 0.000 0.044 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3895 0.5544 0.680 0.000 0.000 0.000 0.320
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.2813 0.6583 0.168 0.000 0.000 0.000 0.832
#> EB7883EB-0079-4548-9132-169E94A698BA 5 0.3165 0.6728 0.036 0.000 0.000 0.116 0.848
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0162 0.8465 0.996 0.000 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0290 0.8186 0.000 0.008 0.000 0.992 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0162 0.8465 0.996 0.000 0.000 0.004 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.0510 0.8191 0.000 0.000 0.984 0.000 0.016
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8247 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0451 0.8724 0.000 0.988 0.000 0.008 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0290 0.8462 0.992 0.008 0.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4021 0.6766 0.780 0.168 0.000 0.052 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.2909 0.7428 0.140 0.000 0.012 0.848 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0162 0.8470 0.996 0.004 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.4677 0.4810 0.000 0.032 0.256 0.684 0.012 0.016
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.0260 0.7042 0.000 0.000 0.000 0.008 0.000 0.992
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8566 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 6 0.1141 0.7149 0.000 0.000 0.000 0.052 0.000 0.948
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2668 0.7926 0.000 0.828 0.000 0.000 0.004 0.168
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0891 0.8167 0.968 0.024 0.008 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0881 0.8370 0.012 0.972 0.008 0.008 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0146 0.8221 0.996 0.000 0.000 0.004 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0146 0.8562 0.000 0.000 0.996 0.004 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.3823 0.1851 0.000 0.000 0.000 0.436 0.564 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.1649 0.7181 0.000 0.036 0.000 0.032 0.932 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0146 0.8221 0.996 0.000 0.000 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.5019 0.6151 0.000 0.604 0.000 0.000 0.104 0.292
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.1341 0.7268 0.028 0.024 0.000 0.000 0.948 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 6 0.3489 0.7124 0.000 0.004 0.000 0.288 0.000 0.708
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0632 0.8190 0.976 0.000 0.000 0.024 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.0520 0.7012 0.000 0.008 0.000 0.008 0.000 0.984
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 5 0.4651 0.4851 0.000 0.056 0.000 0.004 0.636 0.304
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.4735 0.6440 0.000 0.628 0.000 0.076 0.000 0.296
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2854 0.7273 0.000 0.792 0.000 0.000 0.208 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.2799 0.7980 0.000 0.000 0.860 0.064 0.000 0.076
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1141 0.8390 0.000 0.948 0.000 0.000 0.000 0.052
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.3874 0.5750 0.172 0.000 0.000 0.760 0.000 0.068
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.5475 0.6199 0.000 0.620 0.164 0.016 0.000 0.200
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.4060 0.7126 0.032 0.000 0.000 0.284 0.000 0.684
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 5 0.2427 0.7026 0.000 0.032 0.032 0.000 0.900 0.036
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.1267 0.7988 0.940 0.060 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0146 0.8230 0.996 0.000 0.000 0.000 0.004 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0777 0.8206 0.972 0.004 0.000 0.024 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0458 0.8207 0.984 0.000 0.000 0.016 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.5353 0.4806 0.600 0.000 0.000 0.152 0.244 0.004
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.3833 0.6369 0.000 0.708 0.000 0.004 0.272 0.016
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 6 0.1225 0.6764 0.000 0.012 0.000 0.036 0.000 0.952
#> C06D8112-0FA0-4607-988D-589D8694743F 5 0.0713 0.7269 0.028 0.000 0.000 0.000 0.972 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0820 0.8197 0.972 0.000 0.012 0.016 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.5162 0.1177 0.000 0.504 0.000 0.088 0.000 0.408
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.1500 0.8121 0.052 0.936 0.000 0.012 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 6 0.4481 0.6989 0.056 0.000 0.000 0.296 0.000 0.648
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.4165 0.7083 0.036 0.000 0.000 0.292 0.000 0.672
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.1462 0.6662 0.000 0.008 0.000 0.056 0.000 0.936
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0260 0.8224 0.992 0.008 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0260 0.8407 0.000 0.992 0.000 0.008 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.2398 0.5933 0.080 0.000 0.000 0.888 0.004 0.028
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0653 0.8400 0.012 0.980 0.000 0.004 0.000 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.1387 0.8141 0.068 0.000 0.932 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.2801 0.7990 0.000 0.000 0.860 0.068 0.000 0.072
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.4886 -0.3360 0.064 0.000 0.000 0.540 0.000 0.396
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.5409 0.5349 0.076 0.044 0.248 0.632 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0922 0.8422 0.000 0.968 0.000 0.004 0.004 0.024
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 5 0.3204 0.6461 0.068 0.000 0.000 0.092 0.836 0.004
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.1010 0.8171 0.960 0.000 0.036 0.004 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.5356 0.4825 0.000 0.020 0.560 0.072 0.000 0.348
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.1168 0.8149 0.956 0.016 0.028 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.3141 0.6890 0.788 0.000 0.000 0.200 0.000 0.012
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.6893 0.4225 0.232 0.280 0.000 0.424 0.000 0.064
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.8408 0.000 1.000 0.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0508 0.8426 0.004 0.984 0.000 0.000 0.000 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0993 0.8163 0.964 0.012 0.024 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.3835 0.6724 0.000 0.668 0.000 0.000 0.012 0.320
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0603 0.8210 0.980 0.016 0.000 0.004 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.3314 0.7385 0.004 0.740 0.000 0.000 0.000 0.256
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.5990 0.0117 0.440 0.000 0.000 0.296 0.000 0.264
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0508 0.8217 0.984 0.004 0.000 0.012 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 4 0.2553 0.5701 0.012 0.000 0.056 0.888 0.000 0.044
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.5924 0.3875 0.160 0.000 0.016 0.520 0.304 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.3934 0.4418 0.000 0.376 0.000 0.616 0.008 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 4 0.4621 0.5928 0.304 0.064 0.000 0.632 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.2278 0.7564 0.868 0.000 0.004 0.128 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.4535 0.6969 0.060 0.000 0.000 0.296 0.000 0.644
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.6132 0.4593 0.000 0.488 0.064 0.068 0.004 0.376
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.4927 0.5110 0.008 0.248 0.092 0.652 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0692 0.8431 0.000 0.976 0.004 0.000 0.000 0.020
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.4078 0.7077 0.000 0.000 0.748 0.068 0.004 0.180
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.0767 0.8511 0.012 0.008 0.976 0.004 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 6 0.0547 0.7064 0.000 0.000 0.000 0.020 0.000 0.980
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0000 0.8566 0.000 0.000 1.000 0.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.0146 0.7272 0.000 0.000 0.000 0.004 0.996 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0291 0.8560 0.004 0.000 0.992 0.000 0.000 0.004
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.1563 0.8363 0.000 0.000 0.932 0.056 0.000 0.012
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.3073 0.6742 0.788 0.204 0.000 0.008 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 5 0.0405 0.7280 0.000 0.008 0.000 0.000 0.988 0.004
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.1644 0.7819 0.920 0.076 0.000 0.004 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0000 0.8566 0.000 0.000 1.000 0.000 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.4302 0.7076 0.036 0.004 0.000 0.292 0.000 0.668
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0520 0.8389 0.008 0.984 0.000 0.008 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.4854 0.6792 0.088 0.000 0.000 0.292 0.000 0.620
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.8566 0.000 0.000 1.000 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.4617 0.5589 0.664 0.000 0.000 0.252 0.000 0.084
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1461 0.8227 0.000 0.940 0.044 0.016 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4754 0.5693 0.668 0.000 0.000 0.092 0.236 0.004
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.1049 0.8190 0.960 0.008 0.032 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.4794 -0.1908 0.508 0.052 0.000 0.440 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.4745 0.5960 0.000 0.644 0.000 0.000 0.268 0.088
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.3899 0.2633 0.000 0.004 0.000 0.404 0.592 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3741 0.6782 0.000 0.672 0.000 0.000 0.008 0.320
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.2854 0.5991 0.000 0.208 0.000 0.000 0.792 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 6 0.0260 0.7018 0.000 0.000 0.000 0.008 0.000 0.992
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.1204 0.8375 0.000 0.944 0.000 0.000 0.000 0.056
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 5 0.5744 0.4180 0.084 0.000 0.000 0.216 0.624 0.076
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.5611 0.2947 0.528 0.000 0.000 0.292 0.000 0.180
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.2078 0.8069 0.040 0.916 0.012 0.032 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.0260 0.8555 0.000 0.008 0.992 0.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.5549 0.3172 0.536 0.000 0.000 0.296 0.000 0.168
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.4318 0.0822 0.000 0.000 0.448 0.532 0.000 0.020
#> D09064DF-70AE-4A49-9F70-2A8093C96724 6 0.3841 0.7149 0.000 0.000 0.028 0.256 0.000 0.716
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0291 0.8225 0.992 0.000 0.004 0.004 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1065 0.8412 0.000 0.964 0.000 0.008 0.008 0.020
#> C44C898C-EEF9-4E03-911A-9D951312C380 4 0.1555 0.5368 0.004 0.000 0.000 0.932 0.004 0.060
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.4799 0.5820 0.004 0.676 0.000 0.228 0.004 0.088
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0405 0.8393 0.004 0.988 0.000 0.008 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0632 0.8354 0.000 0.976 0.000 0.024 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.3448 0.4549 0.716 0.004 0.000 0.280 0.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.3052 0.7683 0.000 0.780 0.000 0.004 0.000 0.216
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.4563 0.6982 0.000 0.700 0.000 0.000 0.164 0.136
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 4 0.4987 0.5476 0.328 0.000 0.000 0.584 0.088 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.2810 0.8020 0.004 0.832 0.008 0.000 0.000 0.156
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.1858 0.7879 0.092 0.000 0.904 0.000 0.004 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 4 0.4370 0.6103 0.280 0.044 0.000 0.672 0.004 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 6 0.7173 0.4668 0.100 0.000 0.232 0.260 0.000 0.408
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 6 0.4980 0.6703 0.100 0.000 0.000 0.292 0.000 0.608
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0291 0.8400 0.004 0.992 0.000 0.004 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 4 0.3862 0.2482 0.004 0.000 0.000 0.608 0.388 0.000
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#> 72DDC907-0901-4E61-83CF-38500D03FABC 6 0.0547 0.7079 0.000 0.000 0.000 0.020 0.000 0.980
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0291 0.8555 0.000 0.004 0.992 0.004 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.2454 0.8032 0.000 0.840 0.000 0.000 0.000 0.160
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0891 0.8192 0.968 0.024 0.000 0.008 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.3586 0.5978 0.000 0.720 0.268 0.012 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.0891 0.8201 0.968 0.000 0.024 0.008 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0260 0.8560 0.000 0.000 0.992 0.000 0.008 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.2402 0.4312 0.000 0.000 0.000 0.856 0.004 0.140
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0291 0.8400 0.004 0.992 0.000 0.004 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 6 0.0260 0.7042 0.000 0.000 0.000 0.008 0.000 0.992
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0865 0.8142 0.964 0.000 0.000 0.036 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.3227 0.7553 0.828 0.000 0.084 0.088 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 5 0.0790 0.7247 0.000 0.032 0.000 0.000 0.968 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4563 0.7238 0.004 0.720 0.000 0.108 0.004 0.164
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.1644 0.7954 0.920 0.000 0.000 0.076 0.000 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 5 0.2854 0.5882 0.208 0.000 0.000 0.000 0.792 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 5 0.5052 0.2830 0.012 0.000 0.000 0.392 0.544 0.052
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.4747 0.6900 0.080 0.000 0.000 0.288 0.000 0.632
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0458 0.8417 0.000 0.984 0.000 0.000 0.000 0.016
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0508 0.8418 0.000 0.984 0.000 0.000 0.012 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 6 0.0520 0.6944 0.000 0.008 0.000 0.008 0.000 0.984
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0713 0.8206 0.972 0.000 0.028 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.5890 0.1305 0.472 0.000 0.000 0.288 0.000 0.240
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4026 0.5794 0.752 0.000 0.000 0.160 0.088 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.1531 0.8306 0.000 0.000 0.928 0.004 0.068 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.4076 0.1666 0.620 0.000 0.000 0.364 0.016 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.3290 0.4978 0.252 0.000 0.004 0.000 0.744 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4005 0.7053 0.000 0.000 0.748 0.056 0.004 0.192
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.5148 0.5514 0.632 0.000 0.224 0.140 0.000 0.004
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0291 0.8224 0.992 0.004 0.000 0.004 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0146 0.8221 0.996 0.000 0.000 0.004 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0260 0.8395 0.000 0.992 0.000 0.008 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3754 0.7107 0.000 0.000 0.776 0.072 0.000 0.152
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 4 0.4227 0.5730 0.344 0.004 0.000 0.632 0.020 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0363 0.8555 0.000 0.000 0.988 0.012 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0622 0.8223 0.980 0.008 0.000 0.012 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0520 0.7277 0.000 0.008 0.000 0.008 0.984 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0436 0.8416 0.004 0.988 0.004 0.000 0.000 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.5906 0.4953 0.236 0.000 0.000 0.300 0.000 0.464
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0790 0.8144 0.968 0.032 0.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.2631 0.7155 0.820 0.000 0.180 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.4980 0.4750 0.608 0.000 0.000 0.292 0.000 0.100
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.5287 0.5184 0.608 0.000 0.084 0.288 0.000 0.020
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.4571 0.4731 0.000 0.312 0.000 0.636 0.004 0.048
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.3468 0.7138 0.004 0.000 0.000 0.284 0.000 0.712
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 6 0.3023 0.7210 0.000 0.000 0.000 0.232 0.000 0.768
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.5742 0.5422 0.220 0.000 0.000 0.268 0.000 0.512
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.5402 0.4754 0.000 0.576 0.000 0.252 0.000 0.172
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.5482 0.6052 0.160 0.000 0.000 0.292 0.000 0.548
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.6110 0.3207 0.336 0.000 0.000 0.296 0.000 0.368
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 5 0.3971 0.0937 0.448 0.000 0.004 0.000 0.548 0.000
#> 1122039D-5785-4F70-9916-17C585453512 6 0.1267 0.6682 0.000 0.000 0.000 0.060 0.000 0.940
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.4078 0.6036 0.300 0.016 0.000 0.676 0.008 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.2053 0.6761 0.108 0.000 0.000 0.004 0.888 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 6 0.4454 0.0333 0.000 0.348 0.000 0.032 0.004 0.616
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.4892 0.5067 0.000 0.012 0.000 0.072 0.648 0.268
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.1196 0.8372 0.000 0.040 0.952 0.008 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 6 0.2826 0.6775 0.128 0.000 0.000 0.028 0.000 0.844
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 6 0.1806 0.6760 0.000 0.000 0.004 0.088 0.000 0.908
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.5691 0.4812 0.276 0.000 0.000 0.204 0.000 0.520
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.1176 0.8136 0.956 0.000 0.000 0.020 0.024 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0146 0.8560 0.004 0.000 0.996 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5629 0.4783 0.600 0.284 0.060 0.052 0.000 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.1219 0.8382 0.000 0.948 0.000 0.004 0.000 0.048
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.4229 0.7070 0.040 0.000 0.000 0.292 0.000 0.668
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.3043 0.7760 0.000 0.796 0.000 0.004 0.004 0.196
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0291 0.8224 0.992 0.004 0.000 0.004 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.3974 0.5304 0.048 0.000 0.000 0.224 0.728 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.2243 0.7620 0.880 0.004 0.112 0.004 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3547 0.6962 0.000 0.696 0.000 0.004 0.000 0.300
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.1176 0.8124 0.956 0.000 0.000 0.020 0.024 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.5411 0.2928 0.168 0.000 0.000 0.260 0.572 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 5 0.0790 0.7249 0.032 0.000 0.000 0.000 0.968 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0260 0.8220 0.992 0.000 0.000 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.0622 0.6992 0.000 0.012 0.000 0.008 0.000 0.980
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.8225 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4096 0.6434 0.000 0.000 0.700 0.012 0.020 0.268
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.1204 0.8410 0.000 0.000 0.944 0.056 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.3298 0.7453 0.000 0.756 0.000 0.000 0.008 0.236
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0777 0.8185 0.972 0.024 0.000 0.004 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4938 0.5928 0.700 0.200 0.004 0.052 0.000 0.044
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.5154 0.6664 0.104 0.000 0.004 0.292 0.000 0.600
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.1643 0.8033 0.924 0.008 0.000 0.068 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.190 0.676 0.825 0.4159 0.556 0.556
#> 3 3 0.223 0.506 0.656 0.3871 0.664 0.478
#> 4 4 0.305 0.462 0.694 0.1383 0.778 0.541
#> 5 5 0.394 0.495 0.683 0.0848 0.842 0.598
#> 6 6 0.459 0.491 0.689 0.0454 0.920 0.743
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.76246 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.76246 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.9209 0.60813 0.336 0.664
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.9087 0.63046 0.324 0.676
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.77412 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.5519 0.78713 0.128 0.872
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.4431 0.79224 0.092 0.908
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.8955 0.65147 0.312 0.688
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.9775 0.43621 0.412 0.588
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.6531 0.73628 0.832 0.168
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.9248 0.53683 0.340 0.660
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.9044 0.64202 0.320 0.680
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.77412 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.77412 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.9954 0.25827 0.460 0.540
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.9775 0.43730 0.412 0.588
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.8713 0.60569 0.708 0.292
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.5294 0.76722 0.120 0.880
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.9087 0.57118 0.324 0.676
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.77412 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.0000 0.76246 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.77412 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.76246 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.77412 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.5408 0.77316 0.876 0.124
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.77412 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.5737 0.78682 0.136 0.864
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.6148 0.78227 0.152 0.848
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.9044 0.63861 0.320 0.680
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#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.9635 0.38418 0.612 0.388
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.9686 0.35834 0.604 0.396
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.3431 0.77884 0.936 0.064
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.6887 0.74574 0.184 0.816
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.76246 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4815 0.77547 0.104 0.896
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 2 0.8608 0.69144 0.284 0.716
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 2 0.7674 0.74201 0.224 0.776
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.7299 0.76115 0.204 0.796
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.2948 0.79016 0.052 0.948
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 2 0.9933 0.30972 0.452 0.548
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.2778 0.78943 0.048 0.952
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.6247 0.76488 0.844 0.156
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.5946 0.76521 0.144 0.856
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.9460 0.45535 0.636 0.364
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.5946 0.78703 0.144 0.856
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.7950 0.73131 0.240 0.760
#> E4F45B0B-91FA-49C0-9772-27321D23104B 2 0.7950 0.72949 0.240 0.760
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.8955 0.65272 0.312 0.688
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.9427 0.54770 0.360 0.640
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.8661 0.67985 0.288 0.712
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.76246 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.6048 0.78354 0.148 0.852
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.5059 0.77688 0.888 0.112
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 1.0000 -0.09224 0.504 0.496
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.9427 0.56167 0.360 0.640
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.77412 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.77412 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.6623 0.75094 0.828 0.172
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.8207 0.66702 0.744 0.256
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.8081 0.65604 0.752 0.248
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.8661 0.61281 0.712 0.288
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.77412 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.77412 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.8207 0.66346 0.744 0.256
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.9896 0.18662 0.560 0.440
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 2 0.9944 0.29163 0.456 0.544
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.9988 0.16702 0.480 0.520
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.7745 0.74159 0.228 0.772
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.9815 0.40363 0.420 0.580
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.9850 0.38322 0.428 0.572
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.2043 0.78498 0.032 0.968
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 1.0000 -0.08877 0.504 0.496
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.9775 0.29735 0.588 0.412
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 2 0.8327 0.70977 0.264 0.736
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.5629 0.76994 0.132 0.868
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.8661 0.67985 0.288 0.712
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.9963 0.06375 0.536 0.464
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.2603 0.78735 0.044 0.956
#> B23A1419-0406-48BF-813B-B6ED6FD98789 2 0.9000 0.64854 0.316 0.684
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.7219 0.72977 0.200 0.800
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.77412 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.5408 0.77316 0.876 0.124
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.5737 0.78682 0.136 0.864
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.6438 0.77591 0.164 0.836
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.5408 0.77316 0.876 0.124
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.9998 -0.05509 0.508 0.492
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.76246 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.76246 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.76246 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.6623 0.74976 0.828 0.172
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.9044 0.57441 0.320 0.680
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.4562 0.77844 0.904 0.096
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.1184 0.76826 0.984 0.016
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.7602 0.74493 0.220 0.780
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.76246 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.76246 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.9608 0.48549 0.384 0.616
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.9635 0.50141 0.388 0.612
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.8327 0.70588 0.264 0.736
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.7950 0.73131 0.240 0.760
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.9393 0.57857 0.356 0.644
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0000 0.76246 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.3431 0.77959 0.936 0.064
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.5946 0.77022 0.856 0.144
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.9993 0.18692 0.484 0.516
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.4161 0.79204 0.084 0.916
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5842 0.76695 0.140 0.860
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.6887 0.74164 0.816 0.184
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5519 0.76900 0.128 0.872
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.8081 0.72469 0.248 0.752
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.9087 0.63017 0.324 0.676
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.8081 0.66139 0.752 0.248
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.8499 0.69853 0.276 0.724
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.77412 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.8909 0.56401 0.692 0.308
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.8909 0.56401 0.692 0.308
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.5519 0.77525 0.872 0.128
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.6148 0.76732 0.848 0.152
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.8207 0.66346 0.744 0.256
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 2 0.8144 0.72046 0.252 0.748
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4939 0.78953 0.108 0.892
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.9795 0.42628 0.416 0.584
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.77412 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.9977 0.21169 0.472 0.528
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.9608 0.51116 0.384 0.616
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.9170 0.52960 0.668 0.332
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.9044 0.63476 0.320 0.680
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.535 0.707248 0.796 0.176 0.028
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.277 0.731985 0.920 0.008 0.072
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.547 0.611736 0.112 0.072 0.816
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.549 0.613884 0.104 0.080 0.816
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.593 0.865575 0.000 0.644 0.356
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.450 0.428237 0.000 0.196 0.804
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.565 0.105522 0.000 0.312 0.688
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.456 0.615150 0.036 0.112 0.852
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.530 0.616146 0.108 0.068 0.824
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.927 0.536166 0.528 0.240 0.232
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.804 -0.118825 0.064 0.508 0.428
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.401 0.621550 0.028 0.096 0.876
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.581 0.872184 0.000 0.664 0.336
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.593 0.865575 0.000 0.644 0.356
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.784 0.500456 0.120 0.220 0.660
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.566 0.612176 0.100 0.092 0.808
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.663 -0.166244 0.444 0.008 0.548
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.620 0.700342 0.012 0.676 0.312
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.790 -0.102052 0.056 0.508 0.436
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.581 0.872184 0.000 0.664 0.336
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.296 0.732419 0.912 0.008 0.080
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.581 0.872184 0.000 0.664 0.336
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.455 0.718856 0.844 0.132 0.024
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.581 0.872184 0.000 0.664 0.336
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.615 0.616828 0.664 0.008 0.328
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.581 0.872184 0.000 0.664 0.336
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.468 0.440633 0.004 0.192 0.804
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.441 0.479781 0.004 0.172 0.824
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.429 0.618493 0.032 0.104 0.864
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.713 0.691395 0.720 0.164 0.116
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.390 0.536005 0.008 0.128 0.864
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.581 0.872184 0.000 0.664 0.336
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.532 0.616055 0.104 0.072 0.824
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.701 0.527192 0.176 0.100 0.724
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.766 0.536472 0.144 0.172 0.684
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 3 0.638 0.493341 0.032 0.256 0.712
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.623 0.762754 0.000 0.564 0.436
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.498 0.620107 0.096 0.064 0.840
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.287 0.732092 0.916 0.008 0.076
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.636 0.578475 0.628 0.008 0.364
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.463 0.575228 0.012 0.164 0.824
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.315 0.616942 0.036 0.048 0.916
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.581 0.872184 0.000 0.664 0.336
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.455 0.718856 0.844 0.132 0.024
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.295 0.608213 0.020 0.060 0.920
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.534 0.614883 0.084 0.092 0.824
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.506 0.602408 0.148 0.032 0.820
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.922 -0.161079 0.408 0.152 0.440
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.713 0.691395 0.720 0.164 0.116
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.615 0.779688 0.008 0.664 0.328
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.753 0.434291 0.228 0.096 0.676
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.718 -0.079366 0.408 0.028 0.564
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.546 0.552642 0.204 0.020 0.776
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.611 -0.304239 0.000 0.396 0.604
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.602 0.654439 0.700 0.012 0.288
#> 311D089C-33F1-4722-9118-F56427C5C128 3 0.967 0.099828 0.272 0.264 0.464
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.590 0.865982 0.000 0.648 0.352
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.608 0.838188 0.000 0.612 0.388
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.502 0.325303 0.000 0.240 0.760
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.581 0.872184 0.000 0.664 0.336
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.527 0.495620 0.016 0.200 0.784
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.608 0.835923 0.000 0.612 0.388
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.447 0.503762 0.004 0.176 0.820
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.738 0.515665 0.088 0.228 0.684
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.914 -0.081449 0.404 0.144 0.452
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.793 0.653336 0.660 0.140 0.200
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.882 0.626297 0.564 0.280 0.156
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.806 0.478435 0.124 0.236 0.640
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.329 0.627237 0.088 0.012 0.900
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.651 0.525581 0.592 0.008 0.400
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.498 0.608823 0.136 0.036 0.828
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.455 0.718856 0.844 0.132 0.024
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 3 0.631 -0.625927 0.000 0.500 0.500
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.498 0.608823 0.136 0.036 0.828
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.634 -0.046083 0.008 0.360 0.632
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.636 0.578475 0.628 0.008 0.364
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.521 0.615628 0.108 0.064 0.828
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.576 0.583687 0.056 0.152 0.792
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.498 0.561355 0.036 0.136 0.828
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#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.581 0.872184 0.000 0.664 0.336
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.590 0.867815 0.000 0.648 0.352
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.654 0.517133 0.584 0.008 0.408
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.668 0.300714 0.500 0.008 0.492
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.903 0.437160 0.532 0.160 0.308
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.664 -0.183667 0.448 0.008 0.544
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.581 0.872184 0.000 0.664 0.336
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.581 0.872184 0.000 0.664 0.336
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.683 -0.308767 0.492 0.012 0.496
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.654 0.322312 0.304 0.024 0.672
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.507 0.544277 0.196 0.012 0.792
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.817 0.447534 0.120 0.256 0.624
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.456 0.585271 0.036 0.112 0.852
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.734 0.526570 0.100 0.204 0.696
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.665 0.582330 0.136 0.112 0.752
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.631 0.625076 0.000 0.504 0.496
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.546 0.460033 0.244 0.008 0.748
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.669 0.278533 0.308 0.028 0.664
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.436 0.611858 0.052 0.080 0.868
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 3 0.706 -0.249938 0.020 0.460 0.520
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.483 0.611838 0.068 0.084 0.848
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.843 0.377684 0.240 0.148 0.612
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.627 -0.461995 0.000 0.452 0.548
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.389 0.621276 0.024 0.096 0.880
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.737 0.222394 0.032 0.524 0.444
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.586 0.871176 0.000 0.656 0.344
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.623 0.607843 0.652 0.008 0.340
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.468 0.440633 0.004 0.192 0.804
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.341 0.530377 0.000 0.124 0.876
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.623 0.607843 0.652 0.008 0.340
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.701 0.486775 0.208 0.080 0.712
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.547 0.708267 0.792 0.176 0.032
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.287 0.732092 0.916 0.008 0.076
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.287 0.732092 0.916 0.008 0.076
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.651 0.525581 0.592 0.008 0.400
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.789 -0.087348 0.056 0.512 0.432
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.588 0.665249 0.716 0.012 0.272
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.329 0.731132 0.900 0.012 0.088
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.312 0.586767 0.012 0.080 0.908
#> 1122039D-5785-4F70-9916-17C585453512 1 0.296 0.732419 0.912 0.008 0.080
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.455 0.718856 0.844 0.132 0.024
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.757 0.498848 0.088 0.248 0.664
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.498 0.608823 0.136 0.036 0.828
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.475 0.582690 0.024 0.144 0.832
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.537 0.567054 0.048 0.140 0.812
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.523 0.632614 0.104 0.068 0.828
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.296 0.732419 0.912 0.008 0.080
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.468 0.709250 0.804 0.004 0.192
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.693 0.619943 0.640 0.032 0.328
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.516 0.491625 0.216 0.008 0.776
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.533 0.224554 0.000 0.272 0.728
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.707 -0.238753 0.020 0.472 0.508
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.658 0.498103 0.572 0.008 0.420
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.655 0.619858 0.012 0.616 0.372
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.321 0.605663 0.028 0.060 0.912
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.667 0.534824 0.040 0.264 0.696
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.965 0.390229 0.452 0.228 0.320
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.397 0.613643 0.024 0.100 0.876
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.581 0.872184 0.000 0.664 0.336
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.925 0.255065 0.452 0.156 0.392
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.925 0.255065 0.452 0.156 0.392
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.688 0.629969 0.648 0.032 0.320
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.692 0.582424 0.608 0.024 0.368
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.683 -0.308767 0.492 0.012 0.496
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.288 0.609157 0.024 0.052 0.924
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.654 -0.367020 0.008 0.408 0.584
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.512 0.583482 0.160 0.028 0.812
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.581 0.872184 0.000 0.664 0.336
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.806 0.473132 0.132 0.224 0.644
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.455 0.616852 0.132 0.024 0.844
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.651 -0.004992 0.400 0.008 0.592
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.432 0.620706 0.044 0.088 0.868
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.4222 0.4929 0.728 0.000 0.000 0.272
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.4212 0.6402 0.772 0.000 0.216 0.012
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3345 0.5981 0.012 0.124 0.860 0.004
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.3326 0.6009 0.008 0.132 0.856 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.1837 0.7756 0.000 0.944 0.028 0.028
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.5371 0.4037 0.000 0.364 0.616 0.020
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.5696 0.0350 0.000 0.484 0.492 0.024
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.6594 0.5255 0.012 0.152 0.664 0.172
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.7104 0.5003 0.056 0.104 0.656 0.184
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.6626 0.1010 0.384 0.000 0.088 0.528
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.7198 0.4573 0.016 0.244 0.144 0.596
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.6333 0.5236 0.008 0.136 0.680 0.176
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0469 0.7724 0.000 0.988 0.000 0.012
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.1837 0.7756 0.000 0.944 0.028 0.028
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.7140 0.1596 0.040 0.048 0.436 0.476
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.7271 0.4705 0.052 0.104 0.632 0.212
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.5321 0.2939 0.256 0.004 0.704 0.036
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4922 0.5321 0.000 0.736 0.036 0.228
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.7296 0.4363 0.016 0.260 0.144 0.580
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.4364 0.6357 0.764 0.000 0.220 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0469 0.7724 0.000 0.988 0.000 0.012
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2408 0.6216 0.896 0.000 0.000 0.104
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.6079 -0.2774 0.464 0.000 0.492 0.044
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0376 0.7769 0.000 0.992 0.004 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.5436 0.4172 0.000 0.356 0.620 0.024
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.5423 0.4634 0.000 0.332 0.640 0.028
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.6782 0.4893 0.008 0.148 0.632 0.212
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.6079 0.4640 0.628 0.000 0.072 0.300
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.4567 0.5427 0.000 0.276 0.716 0.008
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.3216 0.6010 0.008 0.124 0.864 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.6515 0.4672 0.084 0.048 0.700 0.168
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.7965 0.1533 0.076 0.076 0.504 0.344
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 3 0.7625 0.0237 0.000 0.208 0.432 0.360
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.4174 0.7262 0.000 0.816 0.140 0.044
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.6896 0.5168 0.048 0.108 0.672 0.172
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3982 0.6386 0.776 0.000 0.220 0.004
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.6055 -0.2005 0.436 0.000 0.520 0.044
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.6438 0.5271 0.004 0.208 0.656 0.132
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.4303 0.6042 0.004 0.184 0.792 0.020
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0376 0.7767 0.000 0.992 0.004 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.2408 0.6216 0.896 0.000 0.000 0.104
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.4356 0.5970 0.004 0.200 0.780 0.016
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.7180 0.4725 0.040 0.120 0.636 0.204
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.3030 0.5791 0.020 0.060 0.900 0.020
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.8737 0.2322 0.308 0.036 0.300 0.356
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.6079 0.4640 0.628 0.000 0.072 0.300
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.4050 0.6234 0.000 0.808 0.024 0.168
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.7220 0.4113 0.128 0.048 0.644 0.180
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.6311 0.3325 0.240 0.008 0.660 0.092
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.4227 0.5620 0.076 0.060 0.844 0.020
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.4964 0.3824 0.000 0.616 0.380 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.5928 0.3721 0.508 0.000 0.456 0.036
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.5513 0.5349 0.060 0.012 0.192 0.736
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1833 0.7698 0.000 0.944 0.024 0.032
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.2402 0.7674 0.000 0.912 0.076 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.5744 0.2253 0.000 0.436 0.536 0.028
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.7302 0.3835 0.000 0.332 0.500 0.168
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2281 0.7614 0.000 0.904 0.096 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.6483 0.4614 0.000 0.312 0.592 0.096
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 4 0.6500 0.1229 0.008 0.052 0.448 0.492
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 4 0.8917 0.3278 0.272 0.056 0.272 0.400
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.7255 0.3554 0.556 0.016 0.116 0.312
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.4535 0.1467 0.292 0.000 0.004 0.704
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 4 0.6868 0.2481 0.028 0.048 0.404 0.520
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.4830 0.6056 0.036 0.136 0.800 0.028
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.5969 -0.0814 0.392 0.000 0.564 0.044
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.2563 0.5811 0.012 0.060 0.916 0.012
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.2868 0.6147 0.864 0.000 0.000 0.136
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.4252 0.6355 0.000 0.744 0.252 0.004
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.2563 0.5811 0.012 0.060 0.916 0.012
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.6532 0.1569 0.000 0.504 0.420 0.076
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.6055 -0.2005 0.436 0.000 0.520 0.044
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.7050 0.5004 0.056 0.100 0.660 0.184
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.7722 0.3248 0.016 0.176 0.520 0.288
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.4485 0.5746 0.000 0.248 0.740 0.012
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.4675 0.6463 0.000 0.736 0.244 0.020
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.4979 0.5936 0.004 0.224 0.740 0.032
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.5360 0.2161 0.000 0.436 0.552 0.012
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 3 0.6751 0.2232 0.000 0.396 0.508 0.096
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.7176 0.4556 0.036 0.116 0.628 0.220
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.5113 0.5222 0.000 0.292 0.684 0.024
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0804 0.7787 0.000 0.980 0.012 0.008
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.6007 -0.1286 0.408 0.000 0.548 0.044
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4284 0.5891 0.000 0.224 0.764 0.012
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.4077 0.6025 0.004 0.184 0.800 0.012
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4155 0.6481 0.000 0.756 0.240 0.004
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.5240 0.4146 0.220 0.024 0.736 0.020
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.5105 0.2302 0.000 0.564 0.432 0.004
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#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.4524 0.5929 0.000 0.204 0.768 0.028
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.5430 0.6096 0.036 0.180 0.752 0.032
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.7246 -0.0126 0.008 0.112 0.468 0.412
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3585 0.6008 0.004 0.164 0.828 0.004
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.2408 0.6216 0.896 0.000 0.000 0.104
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.5220 0.4202 0.000 0.352 0.632 0.016
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.6060 0.3821 0.516 0.000 0.440 0.044
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.4959 0.5408 0.096 0.056 0.808 0.040
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.6542 0.5235 0.028 0.116 0.688 0.168
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0469 0.7724 0.000 0.988 0.000 0.012
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.1109 0.7783 0.000 0.968 0.028 0.004
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.5947 -0.0654 0.384 0.000 0.572 0.044
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.6217 0.1820 0.316 0.016 0.624 0.044
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.8347 -0.0830 0.424 0.036 0.176 0.364
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.5279 0.2870 0.252 0.000 0.704 0.044
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.5790 0.1879 0.304 0.004 0.648 0.044
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4832 0.4982 0.144 0.036 0.796 0.024
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.4161 0.5664 0.068 0.064 0.848 0.020
#> EE40EE80-4520-4643-B906-48246BA616A7 4 0.6398 0.2538 0.020 0.032 0.408 0.540
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4284 0.5891 0.000 0.224 0.764 0.012
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.7010 -0.0616 0.016 0.072 0.460 0.452
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.8072 0.3230 0.072 0.108 0.540 0.280
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.4675 0.6463 0.000 0.736 0.244 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.4649 0.5374 0.092 0.048 0.824 0.036
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.6186 0.4563 0.160 0.028 0.716 0.096
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.3969 0.6018 0.000 0.180 0.804 0.016
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.7468 0.1383 0.000 0.464 0.184 0.352
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3585 0.6008 0.004 0.164 0.828 0.004
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.8592 -0.1311 0.140 0.068 0.412 0.380
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.5206 0.5372 0.000 0.668 0.308 0.024
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.6165 0.5290 0.008 0.132 0.696 0.164
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 4 0.7149 0.1394 0.000 0.416 0.132 0.452
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0672 0.7783 0.000 0.984 0.008 0.008
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.6071 -0.2537 0.452 0.000 0.504 0.044
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.5436 0.4172 0.000 0.356 0.620 0.024
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.4722 0.5202 0.000 0.300 0.692 0.008
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.6071 -0.2537 0.452 0.000 0.504 0.044
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.8082 0.4264 0.140 0.092 0.584 0.184
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.4331 0.4850 0.712 0.000 0.000 0.288
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.3982 0.6386 0.776 0.000 0.220 0.004
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.3982 0.6386 0.776 0.000 0.220 0.004
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.5969 -0.0814 0.392 0.000 0.564 0.044
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.7319 0.4306 0.016 0.264 0.144 0.576
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.6140 0.3913 0.500 0.000 0.452 0.048
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4122 0.6322 0.760 0.000 0.236 0.004
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.4475 0.5858 0.004 0.240 0.748 0.008
#> 1122039D-5785-4F70-9916-17C585453512 1 0.4364 0.6357 0.764 0.000 0.220 0.016
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.2704 0.6171 0.876 0.000 0.000 0.124
#> E678189F-D5CF-4C45-8E53-58ECB8448058 4 0.7474 0.1303 0.020 0.104 0.420 0.456
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.2563 0.5811 0.012 0.060 0.916 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.7346 0.4138 0.004 0.224 0.552 0.220
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.4188 0.5786 0.004 0.244 0.752 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.5726 0.5901 0.040 0.120 0.760 0.080
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.4364 0.6357 0.764 0.000 0.220 0.016
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.5436 0.5341 0.620 0.000 0.356 0.024
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.7107 0.3089 0.464 0.012 0.436 0.088
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3720 0.5440 0.064 0.032 0.872 0.032
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.5277 0.1604 0.000 0.460 0.532 0.008
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.7502 0.1114 0.000 0.456 0.188 0.356
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.5911 -0.0375 0.372 0.000 0.584 0.044
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5759 0.4531 0.000 0.668 0.064 0.268
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.4137 0.5976 0.000 0.208 0.780 0.012
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.7213 0.2841 0.008 0.136 0.552 0.304
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 4 0.7044 0.3117 0.276 0.000 0.164 0.560
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.6549 0.5496 0.004 0.200 0.648 0.148
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 4 0.8634 0.2730 0.320 0.036 0.248 0.396
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 4 0.8634 0.2730 0.320 0.036 0.248 0.396
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.6949 0.3130 0.468 0.008 0.440 0.084
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.7009 -0.2267 0.440 0.012 0.468 0.080
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.5790 0.1879 0.304 0.004 0.648 0.044
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.3978 0.5989 0.000 0.192 0.796 0.012
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4776 0.4142 0.000 0.624 0.376 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.2894 0.5712 0.024 0.048 0.908 0.020
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0188 0.7761 0.000 0.996 0.000 0.004
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 4 0.6922 0.1576 0.032 0.044 0.436 0.488
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.4010 0.5954 0.036 0.100 0.848 0.016
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.4831 0.3736 0.208 0.000 0.752 0.040
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.6839 0.5128 0.016 0.144 0.644 0.196
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.5000 0.7817 0.004 0.000 0.068 0.240 0.688
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.2771 0.2367 0.012 0.000 0.000 0.860 0.128
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.3896 0.6328 0.828 0.020 0.024 0.116 0.012
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.3491 0.6457 0.852 0.020 0.028 0.096 0.004
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2605 0.7878 0.056 0.896 0.044 0.000 0.004
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.4587 0.6005 0.748 0.188 0.052 0.000 0.012
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.5524 0.4445 0.632 0.292 0.056 0.000 0.020
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.5052 0.5817 0.744 0.040 0.164 0.048 0.004
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.5794 0.5289 0.692 0.020 0.132 0.144 0.012
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.7537 -0.1356 0.048 0.000 0.400 0.224 0.328
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 3 0.4746 0.4604 0.060 0.076 0.792 0.008 0.064
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4728 0.5884 0.768 0.036 0.156 0.032 0.008
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.1116 0.7788 0.004 0.964 0.028 0.000 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.2605 0.7878 0.056 0.896 0.044 0.000 0.004
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.7032 0.2745 0.388 0.008 0.464 0.084 0.056
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5981 0.4834 0.676 0.012 0.164 0.124 0.024
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.4594 0.2783 0.484 0.000 0.004 0.508 0.004
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4836 0.4406 0.016 0.660 0.308 0.004 0.012
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 3 0.4787 0.4642 0.060 0.088 0.788 0.008 0.056
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0451 0.7912 0.008 0.988 0.004 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.2464 0.2863 0.012 0.000 0.004 0.892 0.092
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1329 0.7765 0.004 0.956 0.032 0.000 0.008
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.4060 0.8473 0.000 0.000 0.000 0.360 0.640
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0451 0.7912 0.008 0.988 0.004 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.3766 0.6342 0.268 0.000 0.000 0.728 0.004
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0510 0.7939 0.016 0.984 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.4892 0.6045 0.740 0.184 0.056 0.008 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.4546 0.6192 0.764 0.164 0.060 0.004 0.008
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.5455 0.5465 0.712 0.048 0.188 0.044 0.008
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 4 0.7318 -0.4047 0.040 0.000 0.188 0.392 0.380
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.3949 0.6513 0.828 0.108 0.036 0.016 0.012
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0451 0.7912 0.008 0.988 0.004 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.3308 0.6432 0.860 0.016 0.024 0.096 0.004
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.6233 0.3991 0.624 0.008 0.140 0.212 0.016
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.7378 0.1114 0.508 0.024 0.304 0.120 0.044
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 3 0.7098 0.2446 0.388 0.136 0.436 0.036 0.004
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.5248 0.6562 0.192 0.700 0.096 0.000 0.012
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.5588 0.5483 0.712 0.020 0.124 0.132 0.012
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.2522 0.2676 0.012 0.000 0.000 0.880 0.108
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.4111 0.6228 0.280 0.000 0.008 0.708 0.004
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.4888 0.6063 0.756 0.068 0.152 0.012 0.012
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2774 0.6727 0.892 0.048 0.012 0.048 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0968 0.7942 0.012 0.972 0.012 0.000 0.004
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.4060 0.8473 0.000 0.000 0.000 0.360 0.640
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.2333 0.6704 0.916 0.052 0.012 0.016 0.004
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.5802 0.5065 0.696 0.020 0.176 0.084 0.024
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 1 0.3792 0.5813 0.808 0.008 0.012 0.160 0.012
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.8379 -0.1352 0.264 0.004 0.296 0.320 0.116
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.7318 -0.4047 0.040 0.000 0.188 0.392 0.380
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.4506 0.5600 0.020 0.728 0.236 0.004 0.012
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.6550 0.2700 0.568 0.008 0.140 0.268 0.016
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.5229 -0.1916 0.500 0.000 0.028 0.464 0.008
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 1 0.4211 0.5308 0.752 0.008 0.008 0.220 0.012
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.5611 -0.0152 0.488 0.456 0.040 0.000 0.016
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.4029 0.6298 0.232 0.000 0.000 0.744 0.024
#> 311D089C-33F1-4722-9118-F56427C5C128 3 0.6567 0.4400 0.112 0.004 0.636 0.080 0.168
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.3154 0.7587 0.032 0.868 0.088 0.004 0.008
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.4166 0.7277 0.144 0.792 0.052 0.000 0.012
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5639 0.5063 0.648 0.268 0.060 0.008 0.016
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0404 0.7934 0.012 0.988 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.6621 0.4302 0.592 0.204 0.172 0.024 0.008
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.3544 0.7294 0.164 0.812 0.016 0.000 0.008
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.5265 0.5857 0.720 0.168 0.092 0.012 0.008
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.6453 0.2507 0.404 0.012 0.496 0.056 0.032
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 3 0.8504 0.2355 0.292 0.004 0.328 0.224 0.152
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.7996 -0.2821 0.096 0.000 0.212 0.368 0.324
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.5383 0.2739 0.008 0.000 0.360 0.048 0.584
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 3 0.6821 0.3655 0.348 0.012 0.520 0.064 0.056
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.3510 0.6326 0.832 0.032 0.000 0.128 0.008
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 4 0.4118 0.5724 0.336 0.000 0.004 0.660 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 1 0.3558 0.5903 0.824 0.008 0.008 0.148 0.012
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.4536 0.8547 0.004 0.000 0.016 0.324 0.656
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.5085 0.5324 0.324 0.632 0.032 0.000 0.012
#> DCD81371-253F-4672-AA92-9F27A338F68E 1 0.3558 0.5903 0.824 0.008 0.008 0.148 0.012
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#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 1 0.5800 0.4662 0.628 0.260 0.096 0.000 0.016
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 4 0.3906 0.6208 0.292 0.000 0.000 0.704 0.004
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 4 0.2522 0.2676 0.012 0.000 0.000 0.880 0.108
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.4546 0.6192 0.764 0.164 0.060 0.004 0.008
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.5885 0.5163 0.680 0.044 0.196 0.072 0.008
#> B57C849C-28B1-4315-885C-330B9C9482B3 1 0.5471 0.2810 0.576 0.368 0.040 0.000 0.016
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4065 0.6881 0.212 0.760 0.020 0.000 0.008
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 5 0.5112 0.7715 0.004 0.000 0.076 0.240 0.680
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0404 0.7934 0.012 0.988 0.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0566 0.7927 0.012 0.984 0.004 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.3689 0.5358 0.128 0.000 0.004 0.820 0.048
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.6519 0.2054 0.368 0.436 0.196 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4738 0.5861 0.760 0.044 0.168 0.020 0.008
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 5 0.4060 0.8473 0.000 0.000 0.000 0.360 0.640
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 1 0.3558 0.5903 0.824 0.008 0.008 0.148 0.012
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.6705 -0.1014 0.456 0.024 0.432 0.060 0.028
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.3730 0.6212 0.288 0.000 0.000 0.712 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 4 0.7324 -0.3642 0.044 0.000 0.180 0.416 0.360
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.4784 0.6699 0.204 0.728 0.056 0.000 0.012
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.6506 0.3172 0.580 0.008 0.144 0.252 0.016
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.4446 0.0972 0.592 0.000 0.000 0.400 0.008
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.4425 0.1257 0.600 0.000 0.000 0.392 0.008
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.4332 0.5545 0.164 0.000 0.004 0.768 0.064
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 3 0.5510 0.4569 0.064 0.228 0.680 0.004 0.024
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 5 0.4060 0.8473 0.000 0.000 0.000 0.360 0.640
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.6785 0.1985 0.148 0.356 0.476 0.004 0.016
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.3872 0.6451 0.836 0.052 0.084 0.024 0.004
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.2900 0.6694 0.876 0.092 0.012 0.020 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.4924 0.6370 0.756 0.144 0.076 0.012 0.012
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.6021 0.2158 0.536 0.364 0.088 0.000 0.012
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.3710 0.5168 0.772 0.004 0.004 0.216 0.004
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.6023 0.1520 0.520 0.388 0.076 0.000 0.016
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.4754 0.5985 0.316 0.000 0.028 0.652 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 3 0.6540 0.3895 0.164 0.268 0.552 0.004 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.7996 -0.1786 0.360 0.004 0.240 0.324 0.072
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 1 0.5846 0.5115 0.644 0.264 0.056 0.020 0.016
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 1 0.4440 0.6568 0.812 0.088 0.036 0.048 0.016
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.2569 0.6700 0.904 0.060 0.020 0.012 0.004
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.4060 0.6683 0.820 0.060 0.012 0.100 0.008
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.6752 0.1503 0.440 0.056 0.444 0.044 0.016
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.3538 0.6621 0.860 0.040 0.024 0.068 0.008
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 5 0.4060 0.8473 0.000 0.000 0.000 0.360 0.640
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 1 0.4429 0.6037 0.772 0.160 0.052 0.000 0.016
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.3684 0.6062 0.192 0.000 0.004 0.788 0.016
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.4168 0.4163 0.704 0.004 0.004 0.284 0.004
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.5259 0.5667 0.744 0.024 0.124 0.096 0.012
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.1116 0.7788 0.004 0.964 0.028 0.000 0.004
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.1942 0.7872 0.068 0.920 0.012 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 4 0.4151 0.5681 0.344 0.000 0.000 0.652 0.004
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 4 0.4545 0.3965 0.432 0.000 0.004 0.560 0.004
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 4 0.8560 -0.1691 0.164 0.004 0.304 0.304 0.224
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.4704 0.2783 0.480 0.000 0.008 0.508 0.004
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0404 0.7934 0.012 0.988 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0404 0.7934 0.012 0.988 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.4758 0.3962 0.432 0.000 0.012 0.552 0.004
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.4370 0.2855 0.656 0.000 0.004 0.332 0.008
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.3802 0.5015 0.760 0.004 0.004 0.228 0.004
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.6524 0.3754 0.340 0.008 0.544 0.064 0.044
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.3758 0.6673 0.844 0.088 0.024 0.036 0.008
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.6607 0.1742 0.440 0.012 0.452 0.056 0.040
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.6879 0.3079 0.592 0.020 0.236 0.108 0.044
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.5884 0.5015 0.324 0.584 0.072 0.000 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.4134 0.4043 0.704 0.004 0.000 0.284 0.008
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.5189 0.1921 0.600 0.004 0.028 0.360 0.008
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.3454 0.6728 0.864 0.052 0.028 0.052 0.004
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 3 0.6561 0.3653 0.160 0.280 0.544 0.004 0.012
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.3538 0.6621 0.860 0.040 0.024 0.068 0.008
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.7947 -0.1969 0.420 0.012 0.340 0.120 0.108
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.6107 0.3219 0.388 0.516 0.076 0.000 0.020
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4482 0.6010 0.788 0.036 0.140 0.028 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 3 0.5425 0.4608 0.064 0.228 0.684 0.004 0.020
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1403 0.7944 0.024 0.952 0.024 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.3838 0.6288 0.280 0.000 0.000 0.716 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.4892 0.6045 0.740 0.184 0.056 0.008 0.012
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.3396 0.6455 0.832 0.136 0.028 0.000 0.004
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.3838 0.6288 0.280 0.000 0.000 0.716 0.004
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.6491 0.3591 0.592 0.008 0.124 0.252 0.024
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 5 0.5112 0.7715 0.004 0.000 0.076 0.240 0.680
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.2522 0.2676 0.012 0.000 0.000 0.880 0.108
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.2522 0.2676 0.012 0.000 0.000 0.880 0.108
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.4118 0.5724 0.336 0.000 0.004 0.660 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 3 0.4852 0.4636 0.060 0.088 0.784 0.008 0.060
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.4649 0.6218 0.232 0.000 0.012 0.720 0.036
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.2616 0.3001 0.020 0.000 0.000 0.880 0.100
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.3010 0.6685 0.868 0.100 0.012 0.020 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.2464 0.2863 0.012 0.000 0.004 0.892 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 5 0.4353 0.8554 0.004 0.000 0.008 0.328 0.660
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.7356 0.2988 0.380 0.052 0.464 0.060 0.044
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.3558 0.5903 0.824 0.008 0.008 0.148 0.012
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.6650 0.4425 0.612 0.124 0.208 0.048 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.4440 0.6568 0.812 0.088 0.036 0.048 0.016
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.5254 0.6310 0.748 0.052 0.060 0.132 0.008
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.2464 0.2863 0.012 0.000 0.004 0.892 0.092
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.3386 0.5373 0.128 0.000 0.000 0.832 0.040
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 4 0.5369 0.6147 0.280 0.000 0.040 0.652 0.028
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.3809 0.4569 0.736 0.000 0.000 0.256 0.008
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.5134 0.4957 0.664 0.280 0.036 0.000 0.020
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.6599 0.3806 0.172 0.268 0.544 0.004 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.4286 0.5647 0.340 0.000 0.004 0.652 0.004
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5610 0.2532 0.040 0.540 0.404 0.004 0.012
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.3067 0.6733 0.880 0.068 0.016 0.032 0.004
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.5771 0.2935 0.596 0.044 0.332 0.008 0.020
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.7972 0.1688 0.112 0.000 0.428 0.212 0.248
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5154 0.6196 0.760 0.064 0.120 0.044 0.012
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0740 0.7930 0.008 0.980 0.008 0.000 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.8555 0.2266 0.228 0.004 0.336 0.264 0.168
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.8555 0.2266 0.228 0.004 0.336 0.264 0.168
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.5112 0.6237 0.276 0.000 0.036 0.668 0.020
#> E6446572-BFA9-4018-89B3-7E4519EBE072 4 0.4791 0.6015 0.316 0.000 0.024 0.652 0.008
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.4758 0.3962 0.432 0.000 0.012 0.552 0.004
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.2481 0.6717 0.908 0.056 0.008 0.024 0.004
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.5688 0.1552 0.452 0.496 0.024 0.016 0.012
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.3825 0.5591 0.796 0.004 0.012 0.176 0.012
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0451 0.7912 0.008 0.988 0.004 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.6978 0.2685 0.388 0.008 0.468 0.084 0.052
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.3767 0.5965 0.800 0.024 0.000 0.168 0.008
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4557 -0.1555 0.516 0.000 0.000 0.476 0.008
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5353 0.5675 0.732 0.040 0.156 0.064 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.3649 0.66628 0.000 0.000 0.196 0.764 0.000 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.4742 0.16705 0.000 0.000 0.052 0.292 0.012 0.644
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.3509 0.56340 0.788 0.000 0.016 0.000 0.016 0.180
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.3898 0.57994 0.776 0.008 0.016 0.004 0.016 0.180
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3249 0.73648 0.096 0.836 0.008 0.000 0.060 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.3232 0.61432 0.840 0.112 0.008 0.000 0.032 0.008
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.4337 0.48607 0.724 0.200 0.008 0.000 0.068 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.5896 0.55479 0.652 0.008 0.104 0.000 0.108 0.128
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6488 0.41849 0.548 0.008 0.132 0.000 0.068 0.244
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 3 0.7244 0.13198 0.016 0.000 0.480 0.236 0.136 0.132
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3592 0.29962 0.012 0.004 0.184 0.016 0.784 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5767 0.55818 0.664 0.008 0.120 0.000 0.088 0.120
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0937 0.74361 0.000 0.960 0.000 0.000 0.040 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.3249 0.73648 0.096 0.836 0.008 0.000 0.060 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.7667 0.24618 0.252 0.000 0.364 0.008 0.228 0.148
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.6547 0.39589 0.532 0.000 0.152 0.000 0.088 0.228
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.3883 0.51273 0.332 0.000 0.012 0.000 0.000 0.656
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4041 0.22488 0.004 0.584 0.004 0.000 0.408 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.3344 0.32818 0.012 0.008 0.164 0.008 0.808 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0405 0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 6 0.4686 0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.1075 0.74007 0.000 0.952 0.000 0.000 0.048 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.1588 0.78057 0.000 0.000 0.004 0.924 0.000 0.072
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0405 0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.3719 0.65380 0.148 0.000 0.012 0.048 0.000 0.792
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0363 0.76717 0.012 0.988 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.3534 0.61989 0.828 0.108 0.008 0.000 0.036 0.020
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3787 0.63407 0.824 0.088 0.016 0.000 0.040 0.032
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.6319 0.51443 0.616 0.016 0.132 0.000 0.096 0.140
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 4 0.7032 0.36190 0.020 0.000 0.284 0.424 0.036 0.236
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.2257 0.64607 0.904 0.048 0.000 0.000 0.008 0.040
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#> 1122039D-5785-4F70-9916-17C585453512 6 0.4686 0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.1682 0.78021 0.000 0.000 0.020 0.928 0.000 0.052
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.7956 0.14088 0.260 0.016 0.300 0.004 0.288 0.132
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.4345 0.49105 0.708 0.000 0.024 0.004 0.020 0.244
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.7689 0.42020 0.500 0.092 0.120 0.000 0.156 0.132
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.3815 0.63077 0.820 0.052 0.012 0.000 0.028 0.088
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.5504 0.53734 0.648 0.020 0.064 0.000 0.032 0.236
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 6 0.4686 0.22953 0.000 0.000 0.056 0.252 0.016 0.676
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.4553 0.50351 0.056 0.000 0.040 0.152 0.004 0.748
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.5541 0.59787 0.168 0.000 0.076 0.060 0.016 0.680
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.4689 0.27564 0.580 0.000 0.020 0.000 0.020 0.380
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.3719 0.52635 0.764 0.200 0.008 0.000 0.028 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 5 0.5923 0.57418 0.152 0.172 0.052 0.000 0.620 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.3262 0.66041 0.196 0.000 0.008 0.008 0.000 0.788
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.4297 0.14221 0.012 0.452 0.004 0.000 0.532 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.2597 0.64424 0.880 0.020 0.004 0.000 0.008 0.088
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.6781 0.30252 0.544 0.024 0.180 0.000 0.192 0.060
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.7613 0.34567 0.056 0.000 0.492 0.132 0.156 0.164
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5550 0.59171 0.696 0.024 0.096 0.000 0.060 0.124
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0508 0.76586 0.004 0.984 0.000 0.000 0.012 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.8467 0.38661 0.152 0.000 0.368 0.140 0.120 0.220
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.8467 0.38661 0.152 0.000 0.368 0.140 0.120 0.220
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.5247 0.60970 0.152 0.000 0.072 0.052 0.016 0.708
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.5229 0.62765 0.196 0.000 0.048 0.056 0.012 0.688
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.4103 0.57871 0.292 0.000 0.008 0.008 0.008 0.684
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.2536 0.64103 0.880 0.020 0.004 0.000 0.004 0.092
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 1 0.5268 -0.08118 0.480 0.456 0.008 0.000 0.016 0.040
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.4520 0.44987 0.676 0.000 0.020 0.004 0.024 0.276
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0405 0.76338 0.004 0.988 0.000 0.000 0.008 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.7471 0.25908 0.248 0.000 0.380 0.000 0.196 0.176
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.3670 0.49411 0.704 0.000 0.012 0.000 0.000 0.284
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.4161 0.42404 0.372 0.000 0.008 0.000 0.008 0.612
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.6066 0.52478 0.628 0.008 0.136 0.000 0.080 0.148
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.878 0.949 0.976 0.4948 0.506 0.506
#> 3 3 0.777 0.831 0.933 0.2343 0.626 0.415
#> 4 4 0.657 0.781 0.889 0.1602 0.755 0.473
#> 5 5 0.875 0.851 0.939 0.0798 0.866 0.592
#> 6 6 0.717 0.607 0.794 0.0549 0.943 0.773
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.983 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.983 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0000 0.969 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.6887 0.799 0.184 0.816
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.969 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.969 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.969 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.983 1.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0000 0.983 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.983 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.0376 0.966 0.004 0.996
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0000 0.969 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.969 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.969 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.983 1.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.983 1.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0000 0.983 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.969 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.0000 0.969 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.969 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.0000 0.983 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.969 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.983 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.969 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.983 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.969 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.0000 0.969 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.969 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.7674 0.744 0.224 0.776
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.983 1.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.0000 0.969 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.969 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.6148 0.837 0.152 0.848
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.983 1.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.983 1.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.0000 0.983 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.969 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.983 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.983 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.0000 0.983 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.0000 0.969 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.7219 0.778 0.200 0.800
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.969 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.983 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.6438 0.824 0.164 0.836
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.7745 0.693 0.772 0.228
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 1 0.0000 0.983 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.983 1.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.983 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.969 0.000 1.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.983 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.983 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 1 0.0000 0.983 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.0000 0.969 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.983 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.983 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.969 0.000 1.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.969 0.000 1.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0000 0.969 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.969 0.000 1.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 2 0.0000 0.969 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.969 0.000 1.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.0000 0.969 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.983 1.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0000 0.983 1.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0000 0.983 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.0000 0.983 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.983 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.983 1.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.983 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.969 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.0000 0.983 1.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.969 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.969 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0000 0.969 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.0000 0.983 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0000 0.983 1.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.9129 0.520 0.328 0.672
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.0000 0.969 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.969 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.6343 0.828 0.160 0.840
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.969 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.0000 0.969 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.0000 0.983 1.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 2 0.2236 0.942 0.036 0.964
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.969 0.000 1.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.983 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.0000 0.969 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 2 0.6531 0.819 0.168 0.832
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.969 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.983 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.0000 0.969 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.0000 0.969 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.969 0.000 1.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 2 0.6531 0.819 0.168 0.832
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.0000 0.983 1.000 0.000
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#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.0000 0.969 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.983 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0000 0.969 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.969 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.983 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.983 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.983 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.983 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.983 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 2 0.6531 0.819 0.168 0.832
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.969 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.8555 0.600 0.720 0.280
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.969 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.983 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.983 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.983 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.983 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.90978 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2356 0.86953 0.928 0.000 0.072
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.90608 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.90608 0.000 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.94343 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.2356 0.85600 0.000 0.072 0.928
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.94343 0.000 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0000 0.90608 0.000 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 0.90608 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.90978 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.7875 0.60423 0.136 0.664 0.200
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.2878 0.83465 0.000 0.096 0.904
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.94343 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.94343 0.000 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.5016 0.65977 0.240 0.000 0.760
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0000 0.90608 0.000 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.0000 0.90608 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.94343 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.7756 0.61487 0.128 0.672 0.200
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.94343 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.6252 0.25948 0.556 0.000 0.444
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.94343 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.90978 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.94343 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.5591 0.50808 0.304 0.000 0.696
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.94343 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.4062 0.76342 0.000 0.164 0.836
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.4002 0.76795 0.000 0.160 0.840
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.0237 0.90368 0.000 0.004 0.996
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0747 0.90321 0.984 0.000 0.016
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0000 0.90608 0.000 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.94343 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.0000 0.90608 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.0000 0.90608 0.000 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.0000 0.90608 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 3 0.0000 0.90608 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.94343 0.000 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0000 0.90608 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.5810 0.52694 0.664 0.000 0.336
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.0000 0.90608 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.1411 0.88305 0.000 0.036 0.964
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.0000 0.90608 0.000 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.94343 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.90978 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.0000 0.90608 0.000 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.90608 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0000 0.90608 0.000 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 3 0.6008 0.38651 0.372 0.000 0.628
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.90978 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.94343 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.0000 0.90608 0.000 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.0000 0.90608 0.000 0.000 1.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.0892 0.89441 0.020 0.000 0.980
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.0000 0.94343 0.000 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.4974 0.63075 0.236 0.000 0.764
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0424 0.90650 0.992 0.000 0.008
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.94343 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.94343 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0000 0.94343 0.000 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.94343 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.4931 0.67939 0.000 0.232 0.768
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.94343 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.2959 0.83085 0.000 0.100 0.900
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.1753 0.87591 0.048 0.000 0.952
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0000 0.90978 1.000 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0237 0.90829 0.996 0.000 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.0000 0.90978 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.6140 0.28196 0.596 0.000 0.404
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.0000 0.90608 0.000 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.0237 0.90338 0.004 0.000 0.996
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.6180 0.27214 0.000 0.416 0.584
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.0000 0.90978 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.94343 0.000 1.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.4887 0.68415 0.000 0.228 0.772
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0000 0.94343 0.000 1.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.0000 0.90608 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0000 0.90608 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.5070 0.68633 0.004 0.224 0.772
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.90608 0.000 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.94343 0.000 1.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.0000 0.90608 0.000 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.94343 0.000 1.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.5882 0.49380 0.000 0.652 0.348
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0000 0.90608 0.000 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.0000 0.90608 0.000 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.94343 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.0000 0.90608 0.000 0.000 1.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.2165 0.86238 0.000 0.064 0.936
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0000 0.90608 0.000 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.94343 0.000 1.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.0000 0.90608 0.000 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.2165 0.86238 0.000 0.064 0.936
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 3 0.5098 0.65789 0.000 0.248 0.752
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.94343 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.0000 0.90608 0.000 0.000 1.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.0000 0.90978 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.94343 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.94343 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.6274 0.09066 0.456 0.000 0.544
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.94343 0.000 1.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.0000 0.90608 0.000 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.6302 -0.00147 0.480 0.000 0.520
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.4555 0.73467 0.000 0.800 0.200
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0592 0.93256 0.000 0.988 0.012
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.0000 0.90608 0.000 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.0000 0.90978 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.0000 0.90608 0.000 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0000 0.90608 0.000 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.4452 0.74390 0.000 0.808 0.192
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.90978 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.0000 0.94343 0.000 1.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0000 0.94343 0.000 1.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.94343 0.000 1.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.0237 0.90829 0.996 0.000 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.4555 0.73467 0.000 0.800 0.200
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.94343 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0000 0.90978 1.000 0.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.94343 0.000 1.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0000 0.90608 0.000 0.000 1.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.90978 1.000 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 3 0.6192 0.21285 0.420 0.000 0.580
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 3 0.0000 0.90608 0.000 0.000 1.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0000 0.94343 0.000 1.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.0000 0.90978 1.000 0.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 2 0.9120 0.40182 0.256 0.544 0.200
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.6079 0.41341 0.612 0.000 0.388
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 2 0.4504 0.73934 0.000 0.804 0.196
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.2356 0.85600 0.000 0.072 0.928
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 3 0.0000 0.90608 0.000 0.000 1.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 3 0.3267 0.80360 0.116 0.000 0.884
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.0000 0.90608 0.000 0.000 1.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.94343 0.000 1.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.3686 0.79078 0.000 0.140 0.860
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.4235 0.74951 0.000 0.176 0.824
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.1289 0.89527 0.968 0.000 0.032
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0000 0.90608 0.000 0.000 1.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 3 0.0000 0.90608 0.000 0.000 1.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.0000 0.94343 0.000 1.000 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 3 0.0000 0.90608 0.000 0.000 1.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.94343 0.000 1.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.2165 0.86238 0.000 0.064 0.936
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.0000 0.90608 0.000 0.000 1.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.94343 0.000 1.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.94343 0.000 1.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 3 0.0000 0.90608 0.000 0.000 1.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.94343 0.000 1.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.94343 0.000 1.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0000 0.90978 1.000 0.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0000 0.90608 0.000 0.000 1.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 3 0.6305 -0.01742 0.484 0.000 0.516
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.94343 0.000 1.000 0.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.2165 0.86238 0.000 0.064 0.936
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 3 0.6026 0.38941 0.000 0.376 0.624
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.0000 0.90978 1.000 0.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 1 0.1964 0.87276 0.944 0.000 0.056
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.0000 0.90978 1.000 0.000 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.1289 0.89527 0.968 0.000 0.032
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#> 97FB3176-395F-475B-8EAE-332C5BEE8155 1 0.0000 0.90978 1.000 0.000 0.000
#> E1876307-DFD9-4688-876F-D71B37466068 2 0.0000 0.94343 0.000 1.000 0.000
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04 2 0.0747 0.92881 0.000 0.984 0.016
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00 3 0.5760 0.45695 0.328 0.000 0.672
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79 3 0.2165 0.86238 0.000 0.064 0.936
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 3 0.0000 0.90608 0.000 0.000 1.000
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 3 0.0000 0.90608 0.000 0.000 1.000
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 3 0.0000 0.90608 0.000 0.000 1.000
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 2 0.0000 0.94343 0.000 1.000 0.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90 3 0.6305 -0.01742 0.484 0.000 0.516
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 2 0.4555 0.73467 0.000 0.800 0.200
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 3 0.0000 0.90608 0.000 0.000 1.000
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.0000 0.94343 0.000 1.000 0.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 2 0.0000 0.94343 0.000 1.000 0.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.94343 0.000 1.000 0.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.94343 0.000 1.000 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0000 0.94343 0.000 1.000 0.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 3 0.3941 0.76437 0.156 0.000 0.844
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.94343 0.000 1.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.2796 0.85483 0.908 0.000 0.092
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.0000 0.90608 0.000 0.000 1.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.2356 0.85600 0.000 0.072 0.928
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.6448 0.69628 0.104 0.132 0.764
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.0000 0.90608 0.000 0.000 1.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.94343 0.000 1.000 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.94343 0.000 1.000 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.0000 0.90608 0.000 0.000 1.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 2 0.9441 0.26767 0.316 0.484 0.200
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.0000 0.94343 0.000 1.000 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 3 0.0000 0.90608 0.000 0.000 1.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.94343 0.000 1.000 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 3 0.5591 0.50808 0.304 0.000 0.696
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0000 0.90608 0.000 0.000 1.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 3 0.0000 0.90608 0.000 0.000 1.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.94343 0.000 1.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.0000 0.90608 0.000 0.000 1.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.90978 1.000 0.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.0000 0.94343 0.000 1.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 3 0.0000 0.90608 0.000 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 1 0.0000 0.90978 1.000 0.000 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.94343 0.000 1.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.0000 0.90608 0.000 0.000 1.000
#> A9195281-8CAE-45A8-8493-744E577907FA 3 0.5138 0.65233 0.000 0.252 0.748
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.94343 0.000 1.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.6260 0.19587 0.000 0.552 0.448
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 3 0.0000 0.90608 0.000 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.6111 0.37455 0.000 0.604 0.396
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 3 0.4931 0.63718 0.232 0.000 0.768
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.2796 0.85446 0.908 0.000 0.092
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.0000 0.90608 0.000 0.000 1.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.0000 0.90608 0.000 0.000 1.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.5621 0.57794 0.000 0.692 0.308
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.94343 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 1 0.0000 0.90978 1.000 0.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.94343 0.000 1.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.94343 0.000 1.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.5397 0.62549 0.720 0.000 0.280
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0000 0.94343 0.000 1.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.0000 0.90608 0.000 0.000 1.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.90978 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.4842 0.68939 0.000 0.224 0.776
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0000 0.90608 0.000 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 3 0.0000 0.90608 0.000 0.000 1.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.90978 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.0000 0.94343 0.000 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.0000 0.90608 0.000 0.000 1.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.90608 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0000 0.90608 0.000 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 3 0.6111 0.28520 0.396 0.000 0.604
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0000 0.94343 0.000 1.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.90978 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.94343 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.0000 0.90608 0.000 0.000 1.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0000 0.90608 0.000 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.4931 0.67939 0.000 0.232 0.768
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.0000 0.94343 0.000 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.0000 0.90608 0.000 0.000 1.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0000 0.94343 0.000 1.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 3 0.5529 0.52394 0.296 0.000 0.704
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.4702 0.71984 0.000 0.788 0.212
#> 72DDC907-0901-4E61-83CF-38500D03FABC 3 0.0000 0.90608 0.000 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0237 0.93987 0.000 0.996 0.004
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.0000 0.90608 0.000 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.0000 0.90608 0.000 0.000 1.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.0000 0.90608 0.000 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.4974 0.67408 0.000 0.236 0.764
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.90608 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.90978 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.6026 0.42697 0.000 0.624 0.376
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.0000 0.90608 0.000 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0000 0.90608 0.000 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.0000 0.90608 0.000 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.94343 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.94343 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.0000 0.90608 0.000 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0000 0.90608 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.90978 1.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.0000 0.90608 0.000 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.94343 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.94343 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.0000 0.90608 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.90608 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.0000 0.90608 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.5291 0.61400 0.268 0.000 0.732
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.90608 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.5291 0.61400 0.268 0.000 0.732
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0000 0.90608 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.94343 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0000 0.90608 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.0000 0.90608 0.000 0.000 1.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0000 0.90608 0.000 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0424 0.93628 0.000 0.992 0.008
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0000 0.90608 0.000 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.5216 0.62756 0.260 0.000 0.740
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.94343 0.000 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.0000 0.90608 0.000 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4555 0.73467 0.000 0.800 0.200
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.94343 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.5650 0.49150 0.312 0.000 0.688
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.2356 0.85600 0.000 0.072 0.928
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.90608 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.3412 0.78880 0.124 0.000 0.876
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0000 0.90608 0.000 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.90978 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.6305 -0.01742 0.484 0.000 0.516
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.6305 -0.01742 0.484 0.000 0.516
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.0000 0.90608 0.000 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.7756 0.61487 0.128 0.672 0.200
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 3 0.6308 -0.04956 0.492 0.000 0.508
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.6305 -0.01742 0.484 0.000 0.516
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.90608 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.5810 0.52694 0.664 0.000 0.336
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.90978 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.3752 0.78596 0.000 0.144 0.856
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0000 0.90608 0.000 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.1529 0.88025 0.000 0.040 0.960
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.90608 0.000 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0000 0.90608 0.000 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.1860 0.88283 0.948 0.000 0.052
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.6126 0.38322 0.600 0.000 0.400
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.6305 -0.01742 0.484 0.000 0.516
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.90608 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.2711 0.84238 0.000 0.088 0.912
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.94343 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.0000 0.90608 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.94343 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.90608 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.2165 0.86266 0.000 0.064 0.936
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.5968 0.39107 0.636 0.000 0.364
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.2356 0.85600 0.000 0.072 0.928
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.94343 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4399 0.73486 0.812 0.000 0.188
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0237 0.90829 0.996 0.000 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.6305 -0.01742 0.484 0.000 0.516
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.6008 0.35072 0.372 0.000 0.628
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.0000 0.90608 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.90608 0.000 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.94343 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.90608 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.94343 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.6305 0.01875 0.516 0.000 0.484
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0000 0.90608 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0000 0.90608 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.0000 0.90608 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3764 0.5561 0.784 0.000 0.000 0.216
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.4961 0.3556 0.552 0.000 0.448 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.2469 0.8194 0.000 0.108 0.892 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.3569 0.7022 0.196 0.000 0.804 0.000
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#> E1876307-DFD9-4688-876F-D71B37466068 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 7E2C9DA9-BC94-48AE-A949-3EC3FA9BCF04 3 0.4250 0.6215 0.000 0.276 0.724 0.000
#> 5447477A-39AC-4B54-98F9-8AE9926D6E00 1 0.0469 0.8085 0.988 0.000 0.012 0.000
#> 80ECFC95-5D27-45CA-A2D2-74176E3FBD79 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 02BB39E5-7DB7-4A83-AB23-2F425CD4E00A 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 5A809CBF-4BB5-4E7F-AA55-E611D2C98D18 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> B6B3D3E1-E2A8-4C01-974B-32A1C9CA930D 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> A113FF0A-B623-49B2-A7DE-0439FBDBF854 2 0.4925 0.2255 0.000 0.572 0.428 0.000
#> B3CCA12D-4569-4AB8-AC41-457448268D90 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> 57F24B18-B295-4FAB-8C48-6DC4C6D8FB9C 3 0.5507 0.6772 0.000 0.156 0.732 0.112
#> A9E61FEB-0C4C-436D-B39F-E70A2839E046 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 919AED7C-37E6-4F90-8BBC-C0975A291946 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 3 0.2589 0.8121 0.000 0.116 0.884 0.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 1 0.7092 0.2943 0.532 0.000 0.320 0.148
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.1474 0.7568 0.948 0.000 0.000 0.052
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.2530 0.8226 0.000 0.000 0.888 0.112
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.4382 0.5248 0.296 0.000 0.704 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 4 0.6603 0.3733 0.000 0.104 0.316 0.580
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.4277 0.6259 0.000 0.280 0.720 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.2578 0.8063 0.912 0.000 0.036 0.052
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.3907 0.6484 0.232 0.000 0.768 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.2773 0.8116 0.000 0.116 0.880 0.004
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.4843 0.4828 0.604 0.000 0.396 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 4 0.2466 0.7721 0.096 0.000 0.004 0.900
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.3975 0.7082 0.760 0.000 0.240 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 3 0.2530 0.8226 0.000 0.000 0.888 0.112
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 3 0.0707 0.8784 0.000 0.020 0.980 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.2149 0.8393 0.000 0.000 0.912 0.088
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0707 0.8133 0.980 0.000 0.020 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.3764 0.5561 0.784 0.000 0.000 0.216
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.3893 0.6994 0.196 0.000 0.796 0.008
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0817 0.8763 0.000 0.024 0.976 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.4746 0.3920 0.000 0.632 0.368 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 4 0.2469 0.8346 0.108 0.000 0.000 0.892
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0188 0.7958 0.996 0.000 0.000 0.004
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.5576 0.1695 0.000 0.444 0.536 0.020
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.3074 0.7731 0.000 0.152 0.848 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.2714 0.8218 0.004 0.000 0.884 0.112
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 4 0.4008 0.7617 0.244 0.000 0.000 0.756
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 3 0.3907 0.6949 0.000 0.232 0.768 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.3688 0.6819 0.208 0.000 0.792 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0188 0.8030 0.996 0.000 0.004 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.1042 0.8963 0.000 0.972 0.008 0.020
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.2053 0.8485 0.000 0.924 0.072 0.004
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.8830 0.000 0.000 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 3 0.3831 0.7276 0.000 0.204 0.792 0.004
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.3726 0.6779 0.000 0.788 0.212 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.1211 0.8224 0.960 0.000 0.040 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 3 0.5678 0.6544 0.000 0.172 0.716 0.112
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.4093 0.7473 0.832 0.000 0.072 0.096
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.4164 0.6500 0.000 0.264 0.736 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.4193 0.5579 0.268 0.000 0.732 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0592 0.8782 0.000 0.000 0.984 0.016
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3764 0.6557 0.216 0.000 0.784 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.0524 0.8813 0.000 0.008 0.988 0.004
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 4 0.4991 0.5815 0.388 0.000 0.004 0.608
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.3975 0.6165 0.240 0.000 0.760 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.4713 0.5609 0.640 0.000 0.360 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.5993 0.6433 0.148 0.000 0.692 0.160
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.6037 0.6377 0.152 0.000 0.688 0.160
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.5783 0.6559 0.188 0.000 0.704 0.108
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.4304 0.6155 0.000 0.284 0.716 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.3311 0.7325 0.172 0.000 0.828 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.6953 0.1185 0.000 0.476 0.412 0.112
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3975 0.6129 0.240 0.000 0.760 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.6626 0.5409 0.216 0.000 0.624 0.160
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.4483 0.5650 0.000 0.712 0.284 0.004
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.0000 0.8830 0.000 0.000 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.6919 0.1950 0.000 0.500 0.388 0.112
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0592 0.8111 0.984 0.000 0.016 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.2345 0.8425 0.900 0.000 0.100 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.2469 0.8346 0.108 0.000 0.000 0.892
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.7581 0.1029 0.000 0.424 0.380 0.196
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0707 0.7859 0.980 0.000 0.000 0.020
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.2530 0.8354 0.112 0.000 0.000 0.888
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.2530 0.8226 0.000 0.000 0.888 0.112
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.4977 0.3225 0.540 0.000 0.460 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.2530 0.8226 0.000 0.000 0.888 0.112
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.4522 0.3510 0.680 0.000 0.000 0.320
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.4746 0.5186 0.632 0.000 0.368 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.0188 0.8837 0.004 0.000 0.996 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0376 0.9122 0.000 0.992 0.004 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2480 0.8301 0.000 0.904 0.008 0.088
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.1211 0.8673 0.000 0.000 0.960 0.040
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 4 0.7648 0.2453 0.216 0.000 0.348 0.436
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0188 0.8821 0.000 0.000 0.996 0.004
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 4 0.7706 0.2357 0.348 0.000 0.228 0.424
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 4 0.7561 0.2702 0.348 0.000 0.200 0.452
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.7999 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0188 0.8030 0.996 0.000 0.004 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0336 0.8832 0.008 0.000 0.992 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.4277 0.5822 0.000 0.720 0.280 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3837 0.6430 0.224 0.000 0.776 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9179 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.7137 0.3719 0.304 0.000 0.536 0.160
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.4790 0.5186 0.620 0.000 0.380 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.2530 0.8455 0.888 0.000 0.112 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.0336 0.8810 0.000 0.000 0.992 0.008
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.3109 0.72668 0.000 0.000 0.000 0.800 0.200
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.2020 0.84906 0.000 0.000 0.900 0.100 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.0290 0.92778 0.008 0.000 0.992 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.3993 0.69096 0.028 0.000 0.756 0.216 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 4 0.6133 0.25471 0.300 0.000 0.160 0.540 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.3134 0.77655 0.848 0.000 0.000 0.120 0.032
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.0000 0.85023 1.000 0.000 0.000 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.1908 0.86586 0.092 0.000 0.908 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5213 0.36227 0.556 0.000 0.048 0.396 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.0000 0.85023 1.000 0.000 0.000 0.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0703 0.92060 0.024 0.000 0.976 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 4 0.3461 0.67534 0.224 0.000 0.000 0.772 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.2377 0.81875 0.000 0.000 0.872 0.128 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.5338 0.25933 0.056 0.000 0.544 0.400 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.2439 0.78914 0.876 0.000 0.004 0.120 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0566 0.93440 0.004 0.984 0.012 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.3266 0.70514 0.004 0.000 0.200 0.796 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.3109 0.72668 0.000 0.000 0.000 0.800 0.200
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.0162 0.92887 0.004 0.000 0.996 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.0290 0.92778 0.008 0.000 0.992 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.1965 0.76876 0.904 0.000 0.096 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.2127 0.83374 0.000 0.000 0.108 0.892 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3300 0.70879 0.792 0.000 0.004 0.204 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.2424 0.81137 0.132 0.000 0.000 0.000 0.868
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 4 0.1341 0.89804 0.056 0.000 0.000 0.944 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 1 0.4542 0.24068 0.536 0.000 0.008 0.456 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.0162 0.92782 0.000 0.004 0.996 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0162 0.84983 0.996 0.000 0.000 0.000 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0703 0.83824 0.976 0.000 0.024 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.2068 0.80766 0.904 0.000 0.000 0.092 0.004
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.4238 0.46811 0.628 0.000 0.000 0.368 0.004
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.0880 0.93505 0.032 0.000 0.000 0.000 0.968
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0162 0.84983 0.996 0.000 0.000 0.000 0.004
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.3796 0.58276 0.000 0.000 0.700 0.300 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.0290 0.92621 0.000 0.008 0.992 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.2732 0.74964 0.000 0.840 0.160 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.0162 0.92782 0.000 0.004 0.996 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.0404 0.92630 0.012 0.000 0.988 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 4 0.3109 0.71099 0.000 0.000 0.200 0.800 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.0162 0.92887 0.004 0.000 0.996 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.0162 0.92782 0.000 0.004 0.996 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 3 0.4262 0.23532 0.440 0.000 0.560 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.0404 0.92630 0.012 0.000 0.988 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.1121 0.89846 0.000 0.956 0.044 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.4305 0.00814 0.512 0.000 0.000 0.000 0.488
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.2074 0.84560 0.000 0.000 0.896 0.104 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.0000 0.85023 1.000 0.000 0.000 0.000 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.2127 0.83779 0.000 0.108 0.892 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0162 0.92887 0.004 0.000 0.996 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 1 0.0162 0.84794 0.996 0.004 0.000 0.000 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.2773 0.78409 0.164 0.836 0.000 0.000 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.2439 0.78835 0.876 0.000 0.000 0.120 0.004
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 1 0.0000 0.85023 1.000 0.000 0.000 0.000 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.2873 0.78258 0.860 0.000 0.000 0.120 0.020
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 1 0.0162 0.84850 0.996 0.000 0.000 0.000 0.004
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.4201 0.29733 0.592 0.000 0.408 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.0404 0.92630 0.012 0.000 0.988 0.000 0.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 4 0.0290 0.93656 0.008 0.000 0.000 0.992 0.000
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 4 0.0290 0.93688 0.000 0.000 0.008 0.992 0.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 2 0.4192 0.31481 0.000 0.596 0.404 0.000 0.000
#> CBEFE77E-A0EB-457D-A145-763654236EBB 4 0.1732 0.87502 0.080 0.000 0.000 0.920 0.000
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 3 0.1608 0.87652 0.000 0.000 0.928 0.072 0.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0162 0.92887 0.004 0.000 0.996 0.000 0.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.94536 0.000 1.000 0.000 0.000 0.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
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#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.0000 0.85023 1.000 0.000 0.000 0.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0290 0.93673 0.000 0.000 0.000 0.992 0.008
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 5 0.0000 0.96505 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0880 0.91095 0.000 0.000 0.968 0.032 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.4182 0.32435 0.000 0.000 0.000 0.600 0.400
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 4 0.1121 0.90739 0.044 0.000 0.000 0.956 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3336 0.68792 0.000 0.000 0.772 0.228 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.2329 0.82835 0.124 0.876 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 1 0.3508 0.56372 0.748 0.252 0.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3837 0.51552 0.692 0.000 0.308 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0162 0.85114 0.996 0.000 0.004 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0794 0.91845 0.028 0.000 0.972 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.2439 0.78914 0.876 0.000 0.004 0.120 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2439 0.78835 0.876 0.000 0.000 0.120 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.2813 0.77010 0.000 0.168 0.832 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.92954 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0162 0.94534 0.004 0.996 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2439 0.78914 0.876 0.000 0.004 0.120 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.2605 0.80046 0.000 0.000 0.852 0.148 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.0000 0.94159 0.000 0.000 0.000 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.3612 0.56531 0.732 0.000 0.268 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.2431 0.74977 0.000 0.000 0.008 0.132 0.000 0.860
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3868 0.32506 0.496 0.000 0.504 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.5061 0.37520 0.428 0.000 0.496 0.000 0.000 0.076
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0865 0.87098 0.000 0.964 0.036 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.2165 0.57801 0.884 0.000 0.108 0.000 0.008 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.3175 0.48331 0.744 0.000 0.256 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.5139 0.35808 0.700 0.000 0.060 0.000 0.148 0.092
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.6980 -0.06363 0.076 0.000 0.376 0.000 0.352 0.196
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.2732 0.77483 0.000 0.000 0.020 0.044 0.880 0.056
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.3200 0.73385 0.000 0.016 0.196 0.000 0.788 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.2230 0.56706 0.892 0.000 0.024 0.000 0.084 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0363 0.87643 0.000 0.988 0.012 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 5 0.0858 0.80411 0.028 0.000 0.004 0.000 0.968 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 5 0.5866 0.51534 0.180 0.000 0.036 0.000 0.596 0.188
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.2006 0.80211 0.004 0.000 0.104 0.000 0.000 0.892
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.3027 0.78451 0.000 0.824 0.148 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.3231 0.73175 0.000 0.016 0.200 0.000 0.784 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 6 0.2969 0.71631 0.000 0.000 0.224 0.000 0.000 0.776
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0000 0.83093 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0777 0.87444 0.004 0.972 0.024 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.2491 0.57737 0.868 0.000 0.112 0.000 0.020 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2728 0.57668 0.860 0.000 0.100 0.000 0.040 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 5 0.2624 0.76259 0.124 0.000 0.020 0.000 0.856 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 6 0.4645 0.41025 0.040 0.000 0.008 0.000 0.336 0.616
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.2697 0.50638 0.812 0.000 0.188 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.5175 0.38018 0.420 0.000 0.492 0.000 0.000 0.088
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.6208 0.20840 0.584 0.000 0.076 0.000 0.172 0.168
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.3161 0.75704 0.092 0.000 0.020 0.000 0.848 0.040
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 5 0.1461 0.80343 0.044 0.000 0.016 0.000 0.940 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.5408 0.54072 0.124 0.560 0.312 0.000 0.004 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.7526 0.01734 0.252 0.000 0.320 0.000 0.144 0.284
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2593 0.73592 0.000 0.000 0.008 0.148 0.000 0.844
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.1610 0.81153 0.000 0.000 0.084 0.000 0.000 0.916
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.1719 0.58011 0.924 0.000 0.016 0.000 0.060 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1500 0.56759 0.936 0.000 0.052 0.000 0.012 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0820 0.58538 0.972 0.000 0.016 0.000 0.012 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 5 0.3543 0.66052 0.200 0.000 0.032 0.000 0.768 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4847 -0.22738 0.056 0.000 0.500 0.000 0.000 0.444
#> 066B10C1-777F-4863-ACCA-6684310B913E 5 0.3280 0.72755 0.032 0.000 0.004 0.000 0.812 0.152
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.3508 0.55700 0.000 0.000 0.000 0.704 0.292 0.004
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.3175 0.77723 0.000 0.808 0.164 0.000 0.028 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.3563 0.72841 0.048 0.000 0.012 0.000 0.132 0.808
#> 4379559E-E467-49BD-9673-40A486146A3B 6 0.2415 0.81424 0.040 0.000 0.036 0.000 0.024 0.900
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.6217 -0.12849 0.004 0.000 0.380 0.000 0.328 0.288
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.3446 0.44917 0.692 0.000 0.308 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 311D089C-33F1-4722-9118-F56427C5C128 5 0.1321 0.80428 0.024 0.000 0.020 0.000 0.952 0.004
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.1204 0.86768 0.000 0.944 0.056 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.2562 0.82326 0.000 0.828 0.172 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.3695 0.46460 0.712 0.000 0.272 0.000 0.016 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0458 0.87560 0.000 0.984 0.016 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 5 0.4594 0.02426 0.480 0.000 0.036 0.000 0.484 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1531 0.86258 0.004 0.928 0.068 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.2365 0.58562 0.888 0.000 0.072 0.000 0.040 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 5 0.1049 0.80466 0.032 0.000 0.008 0.000 0.960 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 5 0.1765 0.79241 0.024 0.000 0.000 0.000 0.924 0.052
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 5 0.3790 0.60171 0.016 0.000 0.004 0.000 0.716 0.264
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.2282 0.86996 0.000 0.000 0.024 0.888 0.088 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 5 0.1010 0.80133 0.004 0.000 0.036 0.000 0.960 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.5473 0.00165 0.568 0.000 0.192 0.000 0.000 0.240
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.0260 0.83158 0.000 0.000 0.008 0.000 0.000 0.992
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.3620 0.36493 0.352 0.000 0.648 0.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.6010 0.16245 0.260 0.428 0.312 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.3727 0.36188 0.388 0.000 0.612 0.000 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.3489 0.45377 0.708 0.004 0.288 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 6 0.2191 0.79478 0.004 0.000 0.120 0.000 0.000 0.876
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 6 0.6905 0.23438 0.076 0.000 0.372 0.000 0.176 0.376
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.1492 0.80582 0.024 0.000 0.036 0.000 0.940 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.3371 0.40091 0.708 0.000 0.292 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.3911 0.72258 0.032 0.712 0.256 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0993 0.58185 0.964 0.000 0.024 0.000 0.012 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 1 0.3706 0.34295 0.620 0.000 0.380 0.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.4828 0.35225 0.604 0.000 0.320 0.000 0.076 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 5 0.0858 0.80410 0.028 0.000 0.004 0.000 0.968 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0725 0.59137 0.976 0.000 0.012 0.000 0.012 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1152 0.87431 0.004 0.952 0.044 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.0622 0.83116 0.008 0.000 0.012 0.000 0.000 0.980
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.3838 -0.08310 0.552 0.000 0.448 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.3198 0.33163 0.740 0.000 0.260 0.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.5667 0.41389 0.192 0.520 0.288 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 6 0.3221 0.76175 0.096 0.000 0.076 0.000 0.000 0.828
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.3126 0.47381 0.752 0.000 0.248 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 5 0.2066 0.80390 0.040 0.000 0.052 0.000 0.908 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.1152 0.57160 0.952 0.000 0.044 0.000 0.004 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.3345 0.68240 0.000 0.000 0.028 0.184 0.788 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2278 0.83736 0.004 0.868 0.128 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.2988 0.78317 0.000 0.828 0.144 0.000 0.028 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.3863 0.72297 0.028 0.712 0.260 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.4892 0.16198 0.660 0.000 0.176 0.000 0.000 0.164
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 6 0.0000 0.83093 0.000 0.000 0.000 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 5 0.4697 0.61895 0.064 0.000 0.324 0.000 0.612 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.5035 0.08701 0.360 0.084 0.556 0.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 6 0.1409 0.82500 0.032 0.000 0.012 0.000 0.008 0.948
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
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#> 17CA5D73-4384-4645-83F8-587847043DD2 6 0.1332 0.82542 0.028 0.000 0.012 0.000 0.008 0.952
#> 40467950-A95C-4731-AD93-0A128442C837 6 0.4873 0.50768 0.020 0.000 0.004 0.044 0.280 0.652
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 1 0.4781 0.36854 0.644 0.076 0.276 0.000 0.004 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.6160 0.21624 0.580 0.000 0.076 0.000 0.220 0.124
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 6 0.2358 0.79735 0.016 0.000 0.108 0.000 0.000 0.876
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 6 0.5002 0.47945 0.080 0.000 0.364 0.000 0.000 0.556
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 5 0.6179 0.18723 0.004 0.328 0.268 0.000 0.400 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.6618 -0.23428 0.028 0.280 0.388 0.000 0.304 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.1720 0.57510 0.928 0.000 0.032 0.000 0.040 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.2883 0.42491 0.788 0.000 0.212 0.000 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.2383 0.58380 0.880 0.000 0.096 0.000 0.024 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.5157 0.32795 0.592 0.044 0.332 0.000 0.032 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.1957 0.52329 0.888 0.000 0.112 0.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.6122 -0.03143 0.360 0.312 0.328 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 6 0.1829 0.81609 0.028 0.000 0.008 0.000 0.036 0.928
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 5 0.3271 0.72081 0.008 0.000 0.232 0.000 0.760 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 5 0.5005 0.26868 0.048 0.000 0.012 0.000 0.544 0.396
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.3950 0.04270 0.432 0.004 0.564 0.000 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 1 0.3428 0.37680 0.696 0.000 0.304 0.000 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.1789 0.58043 0.924 0.000 0.032 0.000 0.044 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.4753 -0.32720 0.496 0.000 0.456 0.000 0.000 0.048
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.2771 0.58099 0.852 0.000 0.116 0.000 0.032 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3869 0.32727 0.500 0.000 0.500 0.000 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 1 0.3508 0.45592 0.704 0.000 0.292 0.000 0.004 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 6 0.0363 0.83086 0.000 0.000 0.012 0.000 0.000 0.988
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 6 0.4705 0.53972 0.260 0.000 0.088 0.000 0.000 0.652
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4816 0.34492 0.680 0.000 0.104 0.000 0.208 0.008
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0547 0.87536 0.000 0.980 0.020 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 6 0.0993 0.82789 0.024 0.000 0.012 0.000 0.000 0.964
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 6 0.0622 0.83167 0.008 0.000 0.012 0.000 0.000 0.980
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 5 0.3875 0.57108 0.000 0.000 0.004 0.016 0.700 0.280
#> 887E7408-C7D7-420F-A763-0EE70A316D17 6 0.3845 0.71122 0.140 0.000 0.088 0.000 0.000 0.772
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0363 0.87567 0.000 0.988 0.012 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0260 0.87590 0.000 0.992 0.008 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 6 0.0363 0.83086 0.000 0.000 0.012 0.000 0.000 0.988
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.3428 0.19562 0.696 0.000 0.304 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.5665 -0.09151 0.532 0.000 0.224 0.000 0.000 0.244
#> EE40EE80-4520-4643-B906-48246BA616A7 5 0.0858 0.80424 0.028 0.000 0.004 0.000 0.968 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.3868 -0.33797 0.508 0.000 0.492 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 5 0.0713 0.80355 0.028 0.000 0.000 0.000 0.972 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.2419 0.78265 0.060 0.000 0.016 0.000 0.896 0.028
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 1 0.4228 0.31288 0.588 0.020 0.392 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 6 0.5530 0.43170 0.224 0.000 0.216 0.000 0.000 0.560
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.5251 0.32209 0.668 0.000 0.064 0.000 0.208 0.060
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.1910 0.52935 0.892 0.000 0.108 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 5 0.3468 0.70708 0.008 0.000 0.264 0.000 0.728 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.3869 -0.35320 0.500 0.000 0.500 0.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 5 0.0891 0.80376 0.024 0.000 0.000 0.000 0.968 0.008
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.6665 -0.30905 0.120 0.372 0.424 0.000 0.084 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.4537 0.34829 0.684 0.000 0.060 0.000 0.248 0.008
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.3596 0.71517 0.004 0.016 0.232 0.000 0.748 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1644 0.86413 0.004 0.920 0.076 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.1065 0.82723 0.020 0.000 0.008 0.000 0.008 0.964
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.1421 0.59187 0.944 0.000 0.028 0.000 0.028 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0692 0.58634 0.976 0.000 0.020 0.000 0.004 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.0891 0.82813 0.024 0.000 0.008 0.000 0.000 0.968
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 6 0.5404 0.66945 0.072 0.000 0.112 0.000 0.136 0.680
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0146 0.96381 0.000 0.000 0.004 0.996 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 6 0.0993 0.82789 0.024 0.000 0.012 0.000 0.000 0.964
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.3231 0.73175 0.000 0.016 0.200 0.000 0.784 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.0146 0.83087 0.000 0.000 0.004 0.000 0.000 0.996
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.2135 0.53289 0.872 0.000 0.128 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 6 0.0458 0.82937 0.000 0.000 0.016 0.000 0.000 0.984
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.96588 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.1720 0.80599 0.032 0.000 0.040 0.000 0.928 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.4829 0.38956 0.424 0.000 0.520 0.000 0.000 0.056
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.1649 0.80618 0.032 0.000 0.036 0.000 0.932 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.3838 -0.20270 0.552 0.000 0.448 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.2003 0.51109 0.884 0.000 0.116 0.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 6 0.3778 0.55207 0.000 0.000 0.016 0.288 0.000 0.696
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.0260 0.83039 0.000 0.000 0.008 0.000 0.000 0.992
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.3163 0.73435 0.024 0.000 0.008 0.000 0.144 0.824
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.5184 0.35341 0.432 0.000 0.480 0.000 0.000 0.088
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.2969 0.52116 0.776 0.000 0.224 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5609 0.51362 0.024 0.500 0.396 0.000 0.080 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0260 0.83158 0.000 0.000 0.008 0.000 0.000 0.992
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.5354 0.57121 0.004 0.140 0.264 0.000 0.592 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.1327 0.56310 0.936 0.000 0.064 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.3606 0.39791 0.728 0.000 0.016 0.000 0.256 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.0951 0.80467 0.020 0.000 0.008 0.000 0.968 0.004
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.1856 0.59182 0.920 0.000 0.048 0.000 0.032 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 5 0.2034 0.78789 0.024 0.000 0.004 0.000 0.912 0.060
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.2094 0.78649 0.024 0.000 0.004 0.000 0.908 0.064
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.0291 0.83089 0.000 0.000 0.004 0.000 0.004 0.992
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.2344 0.79752 0.028 0.000 0.008 0.000 0.068 0.896
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.0363 0.83086 0.000 0.000 0.012 0.000 0.000 0.988
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.1285 0.56793 0.944 0.000 0.052 0.000 0.004 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.5334 0.23020 0.320 0.128 0.552 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.3864 0.34758 0.480 0.000 0.520 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.87542 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 5 0.2461 0.77862 0.044 0.000 0.004 0.000 0.888 0.064
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.5242 0.05233 0.608 0.000 0.216 0.000 0.000 0.176
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.4273 0.67391 0.080 0.000 0.204 0.000 0.000 0.716
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5091 0.20601 0.564 0.000 0.068 0.000 0.360 0.008
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 6.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.918 0.918 0.968 0.5009 0.500 0.500
#> 3 3 0.798 0.849 0.921 0.3046 0.737 0.527
#> 4 4 0.925 0.911 0.962 0.1370 0.850 0.602
#> 5 5 0.930 0.879 0.946 0.0524 0.908 0.674
#> 6 6 0.914 0.855 0.940 0.0423 0.938 0.730
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 6
#> attr(,"optional")
#> [1] 2 4 5
There is also optional best \(k\) = 2 4 5 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.9828 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.9828 1.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0000 0.9511 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.7139 0.7366 0.804 0.196
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#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 1 0.0000 0.9828 1.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.0000 0.9511 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.0000 0.9511 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 1 0.0000 0.9828 1.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9511 0.000 1.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9511 0.000 1.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.9828 1.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0000 0.9511 0.000 1.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0000 0.9828 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.9828 1.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.0000 0.9511 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 1 0.0000 0.9828 1.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0000 0.9828 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.9828 1.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.0000 0.9511 0.000 1.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.0000 0.9828 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.0000 0.9828 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.0000 0.9828 1.000 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0000 0.9828 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0000 0.9511 0.000 1.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.9828 1.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.9511 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 2 0.0376 0.9480 0.004 0.996
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 2 0.9977 0.1666 0.472 0.528
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.0000 0.9511 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.0000 0.9511 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 2 0.9993 0.1259 0.484 0.516
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0000 0.9511 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.9828 1.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0000 0.9511 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.0000 0.9828 1.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.0000 0.9511 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.0000 0.9511 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 2 0.6438 0.7877 0.164 0.836
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 1 0.0000 0.9828 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.0000 0.9511 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 2 0.9988 0.1396 0.480 0.520
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9828 1.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9511 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.9828 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9828 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.0000 0.9828 1.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9511 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9511 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9828 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.9828 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.9828 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9828 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9511 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9511 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.9828 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0000 0.9828 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9828 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.9828 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.5842 0.8165 0.140 0.860
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.9828 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.0000 0.9828 1.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.9511 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0000 0.9828 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9828 1.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 2 0.7376 0.7294 0.208 0.792
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.9511 0.000 1.000
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.9988 0.1397 0.480 0.520
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.0000 0.9828 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.9511 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9828 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0000 0.9511 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9511 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9828 1.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.0000 0.9511 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.0000 0.9511 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9828 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.9828 1.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.9828 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.9828 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.9828 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9828 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.0376 0.9480 0.004 0.996
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9828 1.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9828 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.0000 0.9511 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.9828 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9828 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.9922 0.2097 0.448 0.552
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.0000 0.9828 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.1414 0.9629 0.980 0.020
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9511 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.9828 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0000 0.9828 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.9828 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9828 1.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0000 0.9828 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.0000 0.9511 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9511 0.000 1.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9828 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9511 0.000 1.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.9661 0.3910 0.392 0.608
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.0376 0.9480 0.004 0.996
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.9828 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0000 0.9511 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9511 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9828 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.9828 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.9828 1.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9828 1.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.9828 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 2 0.9993 0.1265 0.484 0.516
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9511 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.0000 0.9828 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9511 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9828 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9828 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.9828 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9828 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.9426 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.6244 -0.1570 0.560 0.000 0.440
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2165 0.7782 0.000 0.064 0.936
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.8228 0.000 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9573 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.9573 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.9573 0.000 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.4452 0.7759 0.192 0.000 0.808
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0000 0.9426 1.000 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.9426 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.4452 0.7106 0.808 0.192 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0000 0.9573 0.000 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9573 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9573 0.000 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.0000 0.9426 1.000 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.9426 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.2959 0.8053 0.100 0.000 0.900
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9573 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.5650 0.5097 0.688 0.312 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9573 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.5650 0.7237 0.312 0.000 0.688
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9573 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9426 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9573 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.5650 0.7237 0.312 0.000 0.688
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9573 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.0000 0.9573 0.000 1.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.9573 0.000 1.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.9426 1.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.0000 0.9426 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.2878 0.7491 0.000 0.096 0.904
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9573 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.0000 0.8228 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.5650 0.7237 0.312 0.000 0.688
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.0000 0.9426 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.0000 0.9426 1.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9573 0.000 1.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.5650 0.7237 0.312 0.000 0.688
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.5650 0.7237 0.312 0.000 0.688
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.5650 0.7237 0.312 0.000 0.688
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.0424 0.9516 0.000 0.992 0.008
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.0000 0.8228 0.000 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9573 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9426 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.0237 0.8208 0.000 0.004 0.996
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.9426 1.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6295 0.4248 0.472 0.000 0.528
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.0000 0.9426 1.000 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.9426 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9573 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.5650 0.7237 0.312 0.000 0.688
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.5650 0.7237 0.312 0.000 0.688
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 1 0.0000 0.9426 1.000 0.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.0000 0.9573 0.000 1.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.5650 0.7237 0.312 0.000 0.688
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.0000 0.9426 1.000 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9573 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.9573 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0000 0.9573 0.000 1.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.9573 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 2 0.3619 0.8197 0.136 0.864 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.9573 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.0000 0.9573 0.000 1.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.0000 0.9426 1.000 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.0000 0.9426 1.000 0.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.0000 0.9426 1.000 0.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.0000 0.9426 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.0000 0.9426 1.000 0.000 0.000
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#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.9426 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9573 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.5650 0.7237 0.312 0.000 0.688
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0000 0.8228 0.000 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.0000 0.9426 1.000 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9573 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9573 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.5650 0.7237 0.312 0.000 0.688
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.5650 0.7237 0.312 0.000 0.688
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.9426 1.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.3752 0.7926 0.144 0.000 0.856
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9573 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9573 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.5650 0.7237 0.312 0.000 0.688
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.8228 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.0000 0.8228 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.0000 0.9426 1.000 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.8228 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.0000 0.9426 1.000 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.0000 0.9426 1.000 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.9573 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0000 0.8228 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.5926 0.6649 0.356 0.000 0.644
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0000 0.8228 0.000 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.4605 0.7282 0.204 0.796 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0000 0.8228 0.000 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.0000 0.9426 1.000 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.9573 0.000 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9426 1.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.6126 0.3033 0.600 0.400 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9573 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.5785 0.6992 0.332 0.000 0.668
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.0424 0.9516 0.000 0.992 0.008
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.2165 0.7783 0.000 0.064 0.936
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.5650 0.7237 0.312 0.000 0.688
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.5785 0.6995 0.332 0.000 0.668
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.9426 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.5650 0.7237 0.312 0.000 0.688
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.5650 0.7237 0.312 0.000 0.688
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.5650 0.7237 0.312 0.000 0.688
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.5650 0.5097 0.688 0.312 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 3 0.5882 0.6768 0.348 0.000 0.652
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.5650 0.7237 0.312 0.000 0.688
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.8228 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 3 0.5650 0.7237 0.312 0.000 0.688
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9426 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.0000 0.9426 1.000 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0000 0.8228 0.000 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.0000 0.9426 1.000 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.8228 0.000 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0000 0.8228 0.000 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.6244 -0.1568 0.560 0.000 0.440
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.5678 0.7192 0.316 0.000 0.684
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0000 0.9426 1.000 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.8228 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.0237 0.9545 0.000 0.996 0.004
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9573 0.000 1.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.4974 0.7586 0.236 0.000 0.764
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9573 0.000 1.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.8228 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.6244 0.2234 0.440 0.560 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.0000 0.9426 1.000 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0000 0.9573 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9573 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.0000 0.9426 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0000 0.9426 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.6299 0.4177 0.476 0.000 0.524
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.5810 0.6938 0.336 0.000 0.664
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.5650 0.7237 0.312 0.000 0.688
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.8228 0.000 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0000 0.9573 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8228 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9573 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0000 0.9426 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0000 0.8228 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0000 0.8228 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9426 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.3726 0.7273 0.788 0.000 0.212 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0336 0.9070 0.000 0.008 0.992 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4356 0.5662 0.708 0.000 0.292 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 4 0.0188 0.9829 0.004 0.000 0.000 0.996
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0188 0.9829 0.004 0.000 0.000 0.996
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.3726 0.7281 0.000 0.212 0.788 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.3764 0.7218 0.784 0.000 0.216 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.1118 0.8909 0.000 0.036 0.964 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.3172 0.7779 0.160 0.000 0.840 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.0188 0.9829 0.004 0.000 0.000 0.996
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.3486 0.7307 0.188 0.000 0.812 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 1 0.0188 0.9560 0.996 0.000 0.000 0.004
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.1302 0.9438 0.044 0.000 0.000 0.956
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.0336 0.9070 0.000 0.008 0.992 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0188 0.9670 0.000 0.996 0.004 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 2 0.3444 0.7679 0.000 0.816 0.000 0.184
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4331 0.5782 0.712 0.000 0.288 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.4277 0.6070 0.000 0.720 0.280 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.3528 0.7558 0.808 0.000 0.000 0.192
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.4356 0.6019 0.000 0.292 0.708 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.3528 0.7254 0.192 0.000 0.808 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0000 0.9590 1.000 0.000 0.000 0.000
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#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0188 0.9562 0.996 0.000 0.004 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 4 0.0921 0.9599 0.028 0.000 0.000 0.972
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0469 0.9042 0.012 0.000 0.988 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0188 0.9561 0.996 0.000 0.004 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0336 0.9536 0.992 0.000 0.008 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.3105 0.8170 0.856 0.000 0.004 0.140
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4790 0.3977 0.000 0.620 0.000 0.380
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0592 0.9028 0.000 0.016 0.984 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.1302 0.9225 0.956 0.000 0.044 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4661 0.4826 0.652 0.000 0.348 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0188 0.9560 0.996 0.000 0.000 0.004
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 4 0.4406 0.5736 0.300 0.000 0.000 0.700
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.4972 0.1210 0.544 0.000 0.456 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.0817 0.8983 0.000 0.024 0.976 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.5784 0.6633 0.000 0.100 0.700 0.200
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.1792 0.8684 0.000 0.068 0.932 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3172 0.7985 0.840 0.000 0.000 0.160
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.9102 0.000 0.000 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.3172 0.7832 0.000 0.160 0.840 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.4866 0.3594 0.596 0.000 0.404 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9706 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 4 0.0000 0.9852 0.000 0.000 0.000 1.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0336 0.9536 0.992 0.000 0.008 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.9590 1.000 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 4 0.0188 0.9829 0.004 0.000 0.000 0.996
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0510 0.9287 0.000 0.000 0.000 0.984 0.016
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0609 0.8444 0.020 0.000 0.980 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0671 0.8444 0.016 0.000 0.980 0.004 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.3983 0.4452 0.340 0.660 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.3837 0.5565 0.692 0.000 0.000 0.308 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 5 0.4644 0.1303 0.000 0.000 0.460 0.012 0.528
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.0162 0.9598 0.000 0.000 0.000 0.004 0.996
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.3300 0.7209 0.792 0.204 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 5 0.0510 0.9583 0.000 0.000 0.000 0.016 0.984
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 4 0.0404 0.9325 0.000 0.000 0.012 0.988 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4287 0.3218 0.000 0.000 0.540 0.460 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.0703 0.9536 0.000 0.000 0.000 0.024 0.976
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0162 0.9681 0.000 0.996 0.004 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0510 0.9072 0.984 0.016 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.3143 0.7232 0.796 0.204 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0404 0.9089 0.988 0.000 0.012 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.0671 0.8444 0.016 0.000 0.980 0.004 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 4 0.0162 0.9382 0.004 0.000 0.000 0.996 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 4 0.0510 0.9300 0.000 0.000 0.016 0.984 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0324 0.9117 0.992 0.004 0.004 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1732 0.8528 0.920 0.000 0.000 0.080 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.0703 0.9536 0.000 0.000 0.000 0.024 0.976
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0703 0.8992 0.976 0.000 0.000 0.024 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 5 0.0000 0.9590 0.000 0.000 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0671 0.8378 0.000 0.000 0.980 0.004 0.016
#> 066B10C1-777F-4863-ACCA-6684310B913E 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 5 0.4359 0.2919 0.000 0.000 0.412 0.004 0.584
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0566 0.9098 0.984 0.012 0.004 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 5 0.0162 0.9584 0.000 0.000 0.004 0.000 0.996
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.3932 0.5568 0.672 0.328 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.1686 0.8881 0.944 0.008 0.020 0.000 0.028
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.3074 0.7326 0.804 0.196 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 5 0.0000 0.9590 0.000 0.000 0.000 0.000 1.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.0000 0.9590 0.000 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 4 0.0771 0.9258 0.004 0.000 0.020 0.976 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.0703 0.8316 0.000 0.024 0.976 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.0671 0.8437 0.016 0.004 0.980 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0290 0.9648 0.008 0.992 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 4 0.0404 0.9325 0.000 0.000 0.012 0.988 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.5982 0.4320 0.000 0.000 0.552 0.136 0.312
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0963 0.8374 0.036 0.000 0.964 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
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#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 4 0.0290 0.9353 0.000 0.000 0.000 0.992 0.008
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0162 0.9680 0.000 0.996 0.004 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.0290 0.9100 0.992 0.000 0.000 0.008 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 5 0.0794 0.9507 0.000 0.000 0.000 0.028 0.972
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.0671 0.8437 0.016 0.004 0.980 0.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 5 0.1568 0.9253 0.036 0.000 0.020 0.000 0.944
#> 17CA5D73-4384-4645-83F8-587847043DD2 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 4 0.0162 0.9382 0.000 0.000 0.000 0.996 0.004
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.4242 0.3958 0.000 0.000 0.572 0.428 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0609 0.9564 0.000 0.980 0.020 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 5 0.0703 0.9536 0.000 0.000 0.000 0.024 0.976
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 2 0.8196 -0.2403 0.220 0.336 0.324 0.120 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0162 0.9119 0.996 0.000 0.004 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0963 0.8956 0.964 0.036 0.000 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0162 0.9119 0.996 0.000 0.004 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 4 0.0162 0.9382 0.000 0.000 0.000 0.996 0.004
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.1012 0.9464 0.000 0.968 0.020 0.000 0.012
#> 72DDC907-0901-4E61-83CF-38500D03FABC 5 0.0880 0.9474 0.000 0.000 0.000 0.032 0.968
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.4045 0.4715 0.000 0.644 0.356 0.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.1106 0.8377 0.024 0.012 0.964 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.3177 0.7192 0.000 0.000 0.792 0.208 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.1282 0.8884 0.952 0.044 0.004 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0609 0.8444 0.020 0.000 0.980 0.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 5 0.0703 0.9536 0.000 0.000 0.000 0.024 0.976
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 5 0.1364 0.9358 0.000 0.000 0.012 0.036 0.952
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> 887E7408-C7D7-420F-A763-0EE70A316D17 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.4550 0.6348 0.036 0.000 0.688 0.276 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 4 0.0963 0.9149 0.000 0.000 0.036 0.964 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0609 0.8444 0.020 0.000 0.980 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.0162 0.9598 0.000 0.000 0.000 0.004 0.996
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.1410 0.9199 0.000 0.940 0.060 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 4 0.0963 0.9151 0.000 0.000 0.036 0.964 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 4 0.4468 0.5989 0.240 0.000 0.000 0.716 0.044
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.2605 0.8001 0.852 0.000 0.148 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0771 0.9533 0.000 0.976 0.020 0.000 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0609 0.8444 0.020 0.000 0.980 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 5 0.0000 0.9590 0.000 0.000 0.000 0.000 1.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 5 0.0794 0.9508 0.000 0.000 0.000 0.028 0.972
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.4707 0.3332 0.000 0.588 0.020 0.000 0.392
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 4 0.0162 0.9382 0.000 0.000 0.000 0.996 0.004
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0162 0.9123 0.996 0.004 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 4 0.0510 0.9287 0.000 0.000 0.000 0.984 0.016
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 5 0.0162 0.9598 0.000 0.000 0.000 0.004 0.996
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 4 0.0290 0.9353 0.000 0.000 0.000 0.992 0.008
#> C33059A9-A313-4806-B43B-0031365F3BE4 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0671 0.8410 0.004 0.000 0.980 0.016 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 5 0.0609 0.9536 0.000 0.000 0.020 0.000 0.980
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0609 0.8444 0.020 0.000 0.980 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.3055 0.7818 0.016 0.000 0.144 0.840 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0510 0.9287 0.000 0.000 0.000 0.984 0.016
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 4 0.3109 0.6879 0.000 0.000 0.000 0.800 0.200
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.3715 0.6623 0.004 0.000 0.736 0.260 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0162 0.9124 0.996 0.004 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0609 0.9564 0.000 0.980 0.020 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0609 0.9055 0.980 0.000 0.020 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.0000 0.9590 0.000 0.000 0.000 0.000 1.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0510 0.9103 0.984 0.000 0.016 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.2516 0.7698 0.000 0.000 0.000 0.860 0.140
#> E6446572-BFA9-4018-89B3-7E4519EBE072 4 0.0162 0.9382 0.000 0.000 0.000 0.996 0.004
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.9405 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9129 1.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.1117 0.8340 0.016 0.020 0.964 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0671 0.8444 0.016 0.000 0.980 0.004 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9705 0.000 1.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 5 0.0404 0.9602 0.000 0.000 0.000 0.012 0.988
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 4 0.0963 0.9149 0.000 0.000 0.036 0.964 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.1121 0.9084 0.000 0.000 0.044 0.956 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 5 0.0833 0.9575 0.004 0.000 0.004 0.016 0.976
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.2562 0.7507 0.000 0.000 0.000 0.172 0.000 0.828
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0713 0.9399 0.028 0.972 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2762 0.7056 0.804 0.000 0.000 0.000 0.000 0.196
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 4 0.3482 0.5278 0.000 0.000 0.316 0.684 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0000 0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 5 0.5005 0.5170 0.248 0.124 0.000 0.000 0.628 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.3797 0.2558 0.000 0.000 0.000 0.580 0.420 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0713 0.9421 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.0000 0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.3797 0.4286 0.000 0.000 0.580 0.000 0.000 0.420
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.2912 0.6862 0.784 0.216 0.000 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 5 0.0260 0.8645 0.000 0.000 0.000 0.008 0.992 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0146 0.8940 0.996 0.000 0.004 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.0000 0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 5 0.0000 0.8695 0.000 0.000 0.000 0.000 1.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.1267 0.8503 0.940 0.000 0.000 0.000 0.000 0.060
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#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 4 0.1007 0.9271 0.000 0.000 0.000 0.956 0.044 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0777 0.8819 0.972 0.004 0.000 0.000 0.024 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.2793 0.7119 0.000 0.000 0.000 0.200 0.000 0.800
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.1444 0.8749 0.000 0.000 0.000 0.072 0.000 0.928
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.8948 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.0363 0.8413 0.000 0.012 0.988 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.8501 0.000 0.000 1.000 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9654 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 4 0.0000 0.9642 0.000 0.000 0.000 1.000 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 6 0.0000 0.9404 0.000 0.000 0.000 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.0260 0.9350 0.000 0.000 0.008 0.000 0.000 0.992
#> 2785594A-571A-46B4-A901-CB9C62DC6174 4 0.1858 0.8735 0.004 0.000 0.000 0.904 0.092 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'pam' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 5.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.960 0.932 0.961 0.3176 0.684 0.684
#> 3 3 0.909 0.911 0.962 0.6821 0.777 0.675
#> 4 4 0.884 0.879 0.954 0.1621 0.795 0.608
#> 5 5 0.906 0.889 0.957 0.1245 0.900 0.743
#> 6 6 0.810 0.822 0.924 0.0939 0.910 0.710
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
#> attr(,"optional")
#> [1] 2 3
There is also optional best \(k\) = 2 3 that is worth to check.
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.2423 0.9418 0.960 0.040
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3431 0.9408 0.936 0.064
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0000 0.9716 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.0000 0.9716 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.2423 0.9509 0.040 0.960
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.9716 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.9716 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.0000 0.9716 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.0000 0.9716 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.2423 0.9418 0.960 0.040
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.7528 0.8036 0.784 0.216
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0000 0.9716 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.2423 0.9509 0.040 0.960
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.2423 0.9509 0.040 0.960
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.8608 0.7044 0.716 0.284
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.6247 0.7916 0.156 0.844
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0000 0.9716 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.2423 0.9509 0.040 0.960
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.7950 0.7715 0.760 0.240
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.2423 0.9509 0.040 0.960
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 2 0.9954 0.0217 0.460 0.540
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.2423 0.9509 0.040 0.960
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.2423 0.9418 0.960 0.040
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2423 0.9509 0.040 0.960
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 2 0.6438 0.7859 0.164 0.836
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.2423 0.9509 0.040 0.960
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.0000 0.9716 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.9716 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.0000 0.9716 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.3879 0.9391 0.924 0.076
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.0000 0.9716 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.2423 0.9509 0.040 0.960
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.0000 0.9716 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 2 0.0000 0.9716 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.0000 0.9716 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.0000 0.9716 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9716 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 2 0.0000 0.9716 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.3431 0.9408 0.936 0.064
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.2778 0.9336 0.048 0.952
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.0000 0.9716 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.0000 0.9716 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.2423 0.9509 0.040 0.960
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.2423 0.9418 0.960 0.040
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0000 0.9716 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.0000 0.9716 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 2 0.0000 0.9716 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.3879 0.9391 0.924 0.076
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.2423 0.9418 0.960 0.040
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2423 0.9509 0.040 0.960
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 2 0.0000 0.9716 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B 2 0.2423 0.9410 0.040 0.960
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.2778 0.9336 0.048 0.952
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.0000 0.9716 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 2 0.2778 0.9336 0.048 0.952
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.3879 0.9391 0.924 0.076
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.2423 0.9509 0.040 0.960
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.2423 0.9509 0.040 0.960
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.0000 0.9716 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.2423 0.9509 0.040 0.960
#> A77DDA16-167D-4444-8C58-526C99F2B406 2 0.0000 0.9716 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.2423 0.9509 0.040 0.960
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.0000 0.9716 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 2 0.9833 0.1308 0.424 0.576
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.3879 0.9391 0.924 0.076
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.3879 0.9391 0.924 0.076
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.2423 0.9418 0.960 0.040
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.5408 0.9042 0.876 0.124
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 2 0.0000 0.9716 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 2 0.2778 0.9336 0.048 0.952
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.0000 0.9716 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.2423 0.9418 0.960 0.040
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.9716 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 2 0.0000 0.9716 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.0000 0.9716 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 2 0.1843 0.9514 0.028 0.972
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 2 0.0000 0.9716 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.0000 0.9716 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 2 0.0000 0.9716 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.9716 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.0000 0.9716 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.0000 0.9716 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.0000 0.9716 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.0000 0.9716 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 2 0.0000 0.9716 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.2423 0.9509 0.040 0.960
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 2 0.2423 0.9410 0.040 0.960
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 2 0.0000 0.9716 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 2 0.0000 0.9716 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.0000 0.9716 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 2 0.0000 0.9716 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.0000 0.9716 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.0000 0.9716 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.2423 0.9509 0.040 0.960
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 2 0.0000 0.9716 0.000 1.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.2423 0.9418 0.960 0.040
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2423 0.9509 0.040 0.960
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.2423 0.9509 0.040 0.960
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 2 0.4562 0.8803 0.096 0.904
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.2236 0.9532 0.036 0.964
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 2 0.0000 0.9716 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.4815 0.9184 0.896 0.104
#> E8327684-CDED-42F2-875C-A99E4D9E5571 2 0.0000 0.9716 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.0000 0.9716 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 2 0.0000 0.9716 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.2423 0.9418 0.960 0.040
#> D09064DF-70AE-4A49-9F70-2A8093C96724 2 0.0000 0.9716 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 2 0.0000 0.9716 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.0000 0.9716 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.2423 0.9418 0.960 0.040
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 2 0.2423 0.9509 0.040 0.960
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 2 0.0000 0.9716 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0376 0.9697 0.004 0.996
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.3879 0.9391 0.924 0.076
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 2 0.0000 0.9716 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.2423 0.9509 0.040 0.960
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#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2423 0.9509 0.040 0.960
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3879 0.9391 0.924 0.076
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.0000 0.9716 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 2 0.0000 0.9716 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.0000 0.9716 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.8741 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.2448 0.8743 0.924 0.000 0.076
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.9661 0.000 0.000 1.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.9661 0.000 0.000 1.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9820 0.000 1.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.9661 0.000 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.0000 0.9661 0.000 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0000 0.9661 0.000 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 0.9661 0.000 0.000 1.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.8741 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.5291 0.6903 0.732 0.000 0.268
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0000 0.9661 0.000 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9820 0.000 1.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9820 0.000 1.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.5835 0.5935 0.660 0.000 0.340
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.3686 0.8119 0.140 0.000 0.860
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.0000 0.9661 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9820 0.000 1.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.5529 0.6555 0.704 0.000 0.296
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9820 0.000 1.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.6309 -0.1026 0.500 0.000 0.500
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9820 0.000 1.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.8741 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9820 0.000 1.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.4555 0.7347 0.200 0.000 0.800
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9820 0.000 1.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 3 0.0000 0.9661 0.000 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 3 0.0000 0.9661 0.000 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 3 0.0000 0.9661 0.000 0.000 1.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2796 0.8722 0.908 0.000 0.092
#> 97C34F1F-2002-4771-8D99-511EA08591CD 3 0.0000 0.9661 0.000 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9820 0.000 1.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.0000 0.9661 0.000 0.000 1.000
#> C06D8112-0FA0-4607-988D-589D8694743F 3 0.0000 0.9661 0.000 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 3 0.0000 0.9661 0.000 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 3 0.0000 0.9661 0.000 0.000 1.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 3 0.0000 0.9661 0.000 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0000 0.9661 0.000 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 1 0.2356 0.8746 0.928 0.000 0.072
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.2356 0.9034 0.072 0.000 0.928
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.0000 0.9661 0.000 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 3 0.0000 0.9661 0.000 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9820 0.000 1.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.8741 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 3 0.0000 0.9661 0.000 0.000 1.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.0000 0.9661 0.000 0.000 1.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.0000 0.9661 0.000 0.000 1.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.2796 0.8722 0.908 0.000 0.092
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.0000 0.8741 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9820 0.000 1.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 3 0.0000 0.9661 0.000 0.000 1.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.2066 0.9149 0.060 0.000 0.940
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.2356 0.9034 0.072 0.000 0.928
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.0000 0.9661 0.000 0.000 1.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.2356 0.9034 0.072 0.000 0.928
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.2796 0.8722 0.908 0.000 0.092
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.9820 0.000 1.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.0000 0.9820 0.000 1.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 3 0.0000 0.9661 0.000 0.000 1.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.9820 0.000 1.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 3 0.0000 0.9661 0.000 0.000 1.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.9820 0.000 1.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 3 0.0000 0.9661 0.000 0.000 1.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 3 0.6008 0.3138 0.372 0.000 0.628
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.2796 0.8722 0.908 0.000 0.092
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.2796 0.8722 0.908 0.000 0.092
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.0000 0.8741 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.4062 0.8111 0.836 0.000 0.164
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.0000 0.9661 0.000 0.000 1.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.2356 0.9034 0.072 0.000 0.928
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.0000 0.9661 0.000 0.000 1.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.0000 0.8741 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 3 0.0000 0.9661 0.000 0.000 1.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.0000 0.9661 0.000 0.000 1.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 3 0.0000 0.9661 0.000 0.000 1.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.1289 0.9400 0.032 0.000 0.968
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.0000 0.9661 0.000 0.000 1.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 3 0.0000 0.9661 0.000 0.000 1.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.0000 0.9661 0.000 0.000 1.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.0000 0.9661 0.000 0.000 1.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 3 0.0000 0.9661 0.000 0.000 1.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.0000 0.9661 0.000 0.000 1.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 3 0.0000 0.9661 0.000 0.000 1.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.0000 0.9661 0.000 0.000 1.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 3 0.0000 0.9661 0.000 0.000 1.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.0000 0.9820 0.000 1.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.2165 0.9111 0.064 0.000 0.936
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0000 0.9661 0.000 0.000 1.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.0000 0.9661 0.000 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 3 0.0000 0.9661 0.000 0.000 1.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.0000 0.9661 0.000 0.000 1.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 3 0.0000 0.9661 0.000 0.000 1.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 3 0.0000 0.9661 0.000 0.000 1.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.9820 0.000 1.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 3 0.0000 0.9661 0.000 0.000 1.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.0000 0.8741 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.0000 0.9820 0.000 1.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.9820 0.000 1.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.3412 0.8442 0.124 0.000 0.876
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 3 0.4702 0.7282 0.000 0.212 0.788
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.0000 0.9661 0.000 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 1 0.3192 0.8556 0.888 0.000 0.112
#> E8327684-CDED-42F2-875C-A99E4D9E5571 3 0.0000 0.9661 0.000 0.000 1.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.0000 0.9661 0.000 0.000 1.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 3 0.0000 0.9661 0.000 0.000 1.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 1 0.0000 0.8741 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.0000 0.9661 0.000 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 3 0.0000 0.9661 0.000 0.000 1.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 3 0.0000 0.9661 0.000 0.000 1.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 1 0.0000 0.8741 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 3 0.6235 0.2632 0.000 0.436 0.564
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 3 0.0000 0.9661 0.000 0.000 1.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.4842 0.6453 0.000 0.776 0.224
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.2796 0.8722 0.908 0.000 0.092
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 3 0.0000 0.9661 0.000 0.000 1.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0000 0.9820 0.000 1.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 1 0.0000 0.8741 1.000 0.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 2 0.1411 0.9329 0.000 0.964 0.036
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 3 0.0000 0.9661 0.000 0.000 1.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 1 0.0000 0.8741 1.000 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 1 0.6295 0.1968 0.528 0.000 0.472
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 3 0.0000 0.9661 0.000 0.000 1.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 2 0.0000 0.9820 0.000 1.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 1 0.0000 0.8741 1.000 0.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 1 0.5497 0.6605 0.708 0.000 0.292
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 1 0.2796 0.8722 0.908 0.000 0.092
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 3 0.0000 0.9661 0.000 0.000 1.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 3 0.0000 0.9661 0.000 0.000 1.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 3 0.2356 0.9034 0.072 0.000 0.928
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 3 0.2356 0.9034 0.072 0.000 0.928
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 3 0.0000 0.9661 0.000 0.000 1.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.9820 0.000 1.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 3 0.0000 0.9661 0.000 0.000 1.000
#> 4C9FCB99-177D-4A76-8E07-3AFAB6CCBBEB 3 0.0000 0.9661 0.000 0.000 1.000
#> 24AB17A1-9C55-4205-B295-9C2B4285F2BB 1 0.2796 0.8722 0.908 0.000 0.092
#> C42EB6B8-2CA4-413E-B217-FE9804BC0716 3 0.0000 0.9661 0.000 0.000 1.000
#> D2ACADF8-4585-4DFD-BC22-57B76C78DEEF 3 0.0000 0.9661 0.000 0.000 1.000
#> 62627085-3DCA-422B-AC4D-8C12CED13B86 3 0.1163 0.9431 0.000 0.028 0.972
#> CBEFE77E-A0EB-457D-A145-763654236EBB 3 0.2356 0.9034 0.072 0.000 0.928
#> 1C7A1C2F-9B9A-4CD5-A0AC-65F79E2535D8 2 0.0000 0.9820 0.000 1.000 0.000
#> F6E0ACA6-1C1E-4401-B187-E2AD84E30F63 3 0.0000 0.9661 0.000 0.000 1.000
#> A882BFC9-8052-49A4-8C71-EBE5534C20A0 3 0.0000 0.9661 0.000 0.000 1.000
#> 25526BF4-9B21-40DD-9036-C2404FD425E5 2 0.0000 0.9820 0.000 1.000 0.000
#> 8A529C29-26BE-42C9-A03E-C9CB406E6843 2 0.0000 0.9820 0.000 1.000 0.000
#> 0DA09625-4E56-45FD-A4F2-8D425776F46D 3 0.0000 0.9661 0.000 0.000 1.000
#> 20F768A8-77E3-4B27-8563-2502C8C518A3 2 0.0000 0.9820 0.000 1.000 0.000
#> CA2F1F6C-3FBC-49E1-928A-320D631C7747 2 0.0000 0.9820 0.000 1.000 0.000
#> 09AC4331-65DA-4D45-9D89-5942B836A2DF 1 0.0000 0.8741 1.000 0.000 0.000
#> 29B5B851-7CBE-49D0-8288-0F3AA8B70F67 3 0.0000 0.9661 0.000 0.000 1.000
#> 4132DCAF-5C32-4B49-A60E-4B4BC4826913 3 0.6111 0.2942 0.396 0.000 0.604
#> 1FE342C8-7A40-433D-9896-6BAF94F6FFC0 2 0.0000 0.9820 0.000 1.000 0.000
#> DB82192F-FE52-4FF5-BAA9-2B266B3678F3 3 0.0000 0.9661 0.000 0.000 1.000
#> F60DD379-3D29-4C5B-8E74-A6C5B3D76406 3 0.0000 0.9661 0.000 0.000 1.000
#> 0AC68E1E-EBE5-4C05-AF60-39B68777E2AA 1 0.0000 0.8741 1.000 0.000 0.000
#> 7EB14F25-A221-4754-BB56-6DEA700355AE 1 0.3752 0.8305 0.856 0.000 0.144
#> 70F9FC41-6202-4B58-9C7C-9946E103E319 1 0.0000 0.8741 1.000 0.000 0.000
#> 23238B08-AA91-46A3-B147-91185A5FAE3F 1 0.2796 0.8722 0.908 0.000 0.092
#> DAB49A2E-BBFD-459B-B156-726D8D91D598 1 0.2796 0.8722 0.908 0.000 0.092
#> 2988B841-8EDC-4C7F-8F86-78FCDDC2631F 3 0.0000 0.9661 0.000 0.000 1.000
#> 4054255A-5B4E-42E9-934C-640DB7D8A8F0 2 0.0000 0.9820 0.000 1.000 0.000
#> D149276E-A961-49D6-8BDA-004E8264A0A1 3 0.0000 0.9661 0.000 0.000 1.000
#> D17803A2-4BF2-4382-A544-76E28695214F 3 0.2537 0.8954 0.080 0.000 0.920
#> ECAB5A67-4E12-4EB0-9998-1618B26774F6 3 0.0000 0.9661 0.000 0.000 1.000
#> 16F5BF94-5103-4973-9432-34FDCC82B6A2 1 0.0000 0.8741 1.000 0.000 0.000
#> 293FB23D-72CB-4211-B4ED-9C57412CE9F0 3 0.0000 0.9661 0.000 0.000 1.000
#> C99F0CD0-B9EB-45F3-885F-6D0519BF1BF7 2 0.0000 0.9820 0.000 1.000 0.000
#> 5B8D1101-572C-4445-81C4-83A6D6115451 3 0.0000 0.9661 0.000 0.000 1.000
#> CA86A053-8669-43F5-947A-9D6D368E7087 3 0.0000 0.9661 0.000 0.000 1.000
#> FDDECB98-0151-4207-BC4E-040E121703DB 3 0.0000 0.9661 0.000 0.000 1.000
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#> 919AED7C-37E6-4F90-8BBC-C0975A291946 3 0.0000 0.9661 0.000 0.000 1.000
#> 5BAD5DAA-9AD8-462B-B2DD-7DF7C37B5DA9 3 0.0000 0.9661 0.000 0.000 1.000
#> 2C91951E-FDDE-4E23-9D7C-648C9BF40351 2 0.0000 0.9820 0.000 1.000 0.000
#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 2 0.0000 0.9820 0.000 1.000 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0000 0.9820 0.000 1.000 0.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 3 0.2356 0.9034 0.072 0.000 0.928
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.9820 0.000 1.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.2796 0.8722 0.908 0.000 0.092
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.0000 0.9661 0.000 0.000 1.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.0000 0.9661 0.000 0.000 1.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.0000 0.9661 0.000 0.000 1.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.0000 0.9661 0.000 0.000 1.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9820 0.000 1.000 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.9820 0.000 1.000 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.0000 0.9661 0.000 0.000 1.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 1 0.4121 0.8070 0.832 0.000 0.168
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.0000 0.9661 0.000 0.000 1.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 3 0.0000 0.9661 0.000 0.000 1.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.9820 0.000 1.000 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.2796 0.8722 0.908 0.000 0.092
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0000 0.9661 0.000 0.000 1.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 3 0.0000 0.9661 0.000 0.000 1.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.9820 0.000 1.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.0000 0.9661 0.000 0.000 1.000
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.8741 1.000 0.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.0000 0.9661 0.000 0.000 1.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 3 0.0000 0.9661 0.000 0.000 1.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 1 0.0000 0.8741 1.000 0.000 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.9820 0.000 1.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.0000 0.9661 0.000 0.000 1.000
#> A9195281-8CAE-45A8-8493-744E577907FA 3 0.0000 0.9661 0.000 0.000 1.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.9820 0.000 1.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 3 0.0000 0.9661 0.000 0.000 1.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 3 0.0000 0.9661 0.000 0.000 1.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.0000 0.9661 0.000 0.000 1.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 3 0.2356 0.9034 0.072 0.000 0.928
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0000 0.8741 1.000 0.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.0000 0.9661 0.000 0.000 1.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.0000 0.9661 0.000 0.000 1.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0000 0.9661 0.000 0.000 1.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 3 0.0000 0.9661 0.000 0.000 1.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 1 0.0000 0.8741 1.000 0.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9820 0.000 1.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9820 0.000 1.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.2796 0.8722 0.908 0.000 0.092
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.0000 0.9661 0.000 0.000 1.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.0000 0.9661 0.000 0.000 1.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.8741 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.0000 0.9661 0.000 0.000 1.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0000 0.9661 0.000 0.000 1.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 3 0.0000 0.9661 0.000 0.000 1.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0000 0.8741 1.000 0.000 0.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 3 0.0000 0.9661 0.000 0.000 1.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.0000 0.9661 0.000 0.000 1.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0000 0.9661 0.000 0.000 1.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.0000 0.9661 0.000 0.000 1.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 3 0.2796 0.8824 0.092 0.000 0.908
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0592 0.9667 0.000 0.988 0.012
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.8741 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.0000 0.9661 0.000 0.000 1.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.0000 0.9661 0.000 0.000 1.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0000 0.9661 0.000 0.000 1.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.9661 0.000 0.000 1.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 3 0.0000 0.9661 0.000 0.000 1.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.0000 0.9661 0.000 0.000 1.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.0000 0.9661 0.000 0.000 1.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 3 0.6045 0.3423 0.380 0.000 0.620
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 3 0.0000 0.9661 0.000 0.000 1.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 3 0.0000 0.9661 0.000 0.000 1.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.9661 0.000 0.000 1.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.0000 0.9661 0.000 0.000 1.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.0000 0.9661 0.000 0.000 1.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.0000 0.9661 0.000 0.000 1.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0000 0.9661 0.000 0.000 1.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.9661 0.000 0.000 1.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.8741 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.0000 0.9661 0.000 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.2356 0.9034 0.072 0.000 0.928
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0000 0.9661 0.000 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.0000 0.9661 0.000 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9820 0.000 1.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9820 0.000 1.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.0747 0.9534 0.016 0.000 0.984
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.2356 0.9034 0.072 0.000 0.928
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.2796 0.8722 0.908 0.000 0.092
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.0000 0.9661 0.000 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9820 0.000 1.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9820 0.000 1.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.2356 0.9034 0.072 0.000 0.928
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.9661 0.000 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.0000 0.9661 0.000 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.4062 0.8111 0.836 0.000 0.164
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.9661 0.000 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.6008 0.5260 0.628 0.000 0.372
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0000 0.9661 0.000 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.9661 0.000 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0000 0.9661 0.000 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.0000 0.9661 0.000 0.000 1.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0000 0.9661 0.000 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 3 0.4062 0.7719 0.164 0.000 0.836
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0000 0.9661 0.000 0.000 1.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.4399 0.7854 0.812 0.000 0.188
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0000 0.9661 0.000 0.000 1.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.0000 0.9661 0.000 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 3 0.0000 0.9661 0.000 0.000 1.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9820 0.000 1.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.6260 0.1133 0.448 0.000 0.552
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0000 0.9661 0.000 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.9661 0.000 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.2356 0.9034 0.072 0.000 0.928
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.0000 0.9661 0.000 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.8741 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.6168 0.3858 0.588 0.000 0.412
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.6244 0.1438 0.440 0.000 0.560
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.0000 0.9661 0.000 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.8228 0.3551 0.512 0.076 0.412
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.2796 0.8722 0.908 0.000 0.092
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.4555 0.7594 0.800 0.000 0.200
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.9661 0.000 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.2796 0.8722 0.908 0.000 0.092
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.8741 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.6244 0.0743 0.440 0.000 0.560
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0000 0.9661 0.000 0.000 1.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.0000 0.9661 0.000 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.9661 0.000 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0000 0.9661 0.000 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0000 0.8741 1.000 0.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.2796 0.8722 0.908 0.000 0.092
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2796 0.8722 0.908 0.000 0.092
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.9661 0.000 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.0000 0.9661 0.000 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.1964 0.9159 0.000 0.056 0.944
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.0000 0.9661 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4504 0.6926 0.000 0.804 0.196
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.9661 0.000 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.0000 0.9661 0.000 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.4062 0.8111 0.836 0.000 0.164
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.9661 0.000 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9820 0.000 1.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3340 0.8518 0.880 0.000 0.120
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2796 0.8722 0.908 0.000 0.092
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.5138 0.6947 0.748 0.000 0.252
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.6111 0.2943 0.396 0.000 0.604
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.2356 0.9034 0.072 0.000 0.928
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.9661 0.000 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.0000 0.9661 0.000 0.000 1.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.9661 0.000 0.000 1.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9820 0.000 1.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2959 0.8672 0.900 0.000 0.100
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0000 0.9661 0.000 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0000 0.9661 0.000 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.0000 0.9661 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.0921 0.8016 0.972 0.000 0.000 0.028
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.4543 0.5687 0.324 0.000 0.000 0.676
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 3 0.1389 0.9214 0.048 0.000 0.952 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.1118 0.8034 0.964 0.000 0.036 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.0000 0.8197 1.000 0.000 0.000 0.000
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#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 3 0.4730 0.3847 0.364 0.000 0.636 0.000
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 1 0.2647 0.7373 0.880 0.000 0.120 0.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 3 0.1716 0.9053 0.064 0.000 0.936 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.4624 0.4850 0.660 0.000 0.340 0.000
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.4996 0.1623 0.516 0.000 0.484 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 3 0.4830 0.2762 0.392 0.000 0.608 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 4 0.3610 0.7733 0.200 0.000 0.000 0.800
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.1792 0.9010 0.068 0.000 0.932 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.3528 0.6228 0.808 0.000 0.000 0.192
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.1557 0.9142 0.056 0.000 0.944 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 80936433-AA91-4219-98F1-706C36298060 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 241F589C-D559-43D7-8340-31EBCEB36E14 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.4916 0.3469 0.576 0.000 0.424 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.2647 0.7210 0.880 0.000 0.000 0.120
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.4977 0.2374 0.540 0.000 0.460 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.3311 0.7602 0.172 0.000 0.828 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0469 0.9630 0.000 0.988 0.012 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 3 0.4730 0.3827 0.364 0.000 0.636 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.3219 0.6861 0.836 0.000 0.164 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 3 0.0469 0.9516 0.012 0.000 0.988 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 3 0.0921 0.9384 0.028 0.000 0.972 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.2760 0.7190 0.872 0.000 0.128 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.2408 0.8544 0.104 0.000 0.896 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0188 0.9324 0.004 0.000 0.000 0.996
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.4164 0.6122 0.264 0.000 0.736 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 3 0.4605 0.4776 0.000 0.336 0.664 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.9342 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.3528 0.6228 0.808 0.000 0.000 0.192
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.3764 0.6288 0.784 0.000 0.216 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.1557 0.9097 0.000 0.056 0.944 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0336 0.8176 0.992 0.000 0.008 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.3569 0.6599 0.000 0.804 0.196 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 3 0.1792 0.9008 0.068 0.000 0.932 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 3 0.3610 0.7259 0.200 0.000 0.800 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 3 0.4830 0.3051 0.392 0.000 0.608 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.3942 0.6063 0.764 0.000 0.236 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.0000 0.8197 1.000 0.000 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9799 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 3 0.3444 0.7512 0.184 0.000 0.816 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0000 0.9608 0.000 0.000 1.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.4925 0.3449 0.572 0.000 0.428 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.0000 0.9608 0.000 0.000 1.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0000 0.998 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.0162 0.859 0.000 0.000 0.000 0.996 0.004
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.980 0.000 1.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.0162 0.963 0.004 0.000 0.996 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.0404 0.960 0.012 0.000 0.988 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.0162 0.963 0.000 0.000 0.996 0.004 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0404 0.957 0.012 0.000 0.988 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0404 0.891 0.988 0.000 0.000 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.0404 0.892 0.988 0.000 0.012 0.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.980 0.000 1.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.980 0.000 1.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.2286 0.782 0.888 0.000 0.108 0.004 0.000
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#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.0404 0.891 0.988 0.000 0.000 0.012 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.0404 0.854 0.012 0.000 0.000 0.988 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 4 0.3395 0.605 0.000 0.000 0.236 0.764 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.0000 0.861 0.000 0.000 0.000 1.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.0404 0.960 0.012 0.000 0.988 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.980 0.000 1.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0404 0.891 0.988 0.000 0.000 0.012 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.4242 0.324 0.000 0.000 0.428 0.572 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.0000 0.965 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 1 0.2260 0.8005 0.860 0.000 0.140 0.000 0.000 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.1714 0.8609 0.908 0.000 0.092 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.3482 0.4955 0.684 0.000 0.316 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.0363 0.9370 0.988 0.000 0.000 0.000 0.012 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0146 0.9532 0.004 0.996 0.000 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 5 0.1267 0.8351 0.060 0.000 0.000 0.000 0.940 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0260 0.9521 0.000 0.992 0.008 0.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.1700 0.8368 0.000 0.004 0.080 0.000 0.916 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 3 0.3351 0.5728 0.000 0.288 0.712 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 6 0.3804 0.2682 0.000 0.000 0.000 0.000 0.424 0.576
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0260 0.9399 0.992 0.000 0.008 0.000 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 1 0.0260 0.9396 0.992 0.000 0.008 0.000 0.000 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.1957 0.7686 0.112 0.000 0.000 0.000 0.888 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.3592 0.4309 0.656 0.000 0.344 0.000 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.2793 0.6666 0.000 0.000 0.000 0.200 0.000 0.800
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1814 0.8840 0.000 0.900 0.100 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 1 0.4184 0.2385 0.576 0.000 0.016 0.000 0.000 0.408
#> 066B10C1-777F-4863-ACCA-6684310B913E 5 0.5484 0.4014 0.228 0.000 0.000 0.000 0.568 0.204
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.2762 0.6718 0.196 0.000 0.000 0.000 0.000 0.804
#> 4379559E-E467-49BD-9673-40A486146A3B 6 0.0713 0.8463 0.028 0.000 0.000 0.000 0.000 0.972
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 3 0.2730 0.6987 0.192 0.000 0.808 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 311D089C-33F1-4722-9118-F56427C5C128 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 3 0.0865 0.7419 0.000 0.036 0.964 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 3 0.3782 0.2021 0.000 0.412 0.588 0.000 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0547 0.9318 0.980 0.000 0.020 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 3 0.3810 0.3164 0.000 0.428 0.572 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 5 0.0260 0.8891 0.008 0.000 0.000 0.000 0.992 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 1 0.0260 0.9396 0.992 0.000 0.008 0.000 0.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 3 0.2003 0.7662 0.116 0.000 0.884 0.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.3782 0.3924 0.412 0.000 0.588 0.000 0.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.3756 0.2768 0.600 0.000 0.400 0.000 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 1 0.0458 0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 1 0.3804 0.1351 0.576 0.000 0.424 0.000 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.2003 0.7662 0.116 0.000 0.884 0.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.2003 0.7662 0.116 0.000 0.884 0.000 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.3737 0.3569 0.608 0.000 0.000 0.000 0.392 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 3 0.3810 0.2778 0.000 0.428 0.572 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 1 0.2527 0.7645 0.832 0.000 0.168 0.000 0.000 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 3 0.0603 0.7505 0.016 0.004 0.980 0.000 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.2219 0.8091 0.864 0.000 0.000 0.000 0.000 0.136
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.0547 0.9317 0.980 0.000 0.020 0.000 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 5 0.2996 0.6277 0.228 0.000 0.000 0.000 0.772 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 3 0.3797 0.3322 0.000 0.420 0.580 0.000 0.000 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.1714 0.8909 0.000 0.908 0.092 0.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 3 0.2003 0.7662 0.116 0.000 0.884 0.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 5 0.5421 0.2460 0.432 0.004 0.100 0.000 0.464 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.0260 0.7468 0.008 0.000 0.992 0.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.3499 0.5029 0.680 0.000 0.000 0.000 0.000 0.320
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 5 0.4612 0.6264 0.188 0.004 0.108 0.000 0.700 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 3 0.4747 0.4419 0.376 0.056 0.568 0.000 0.000 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 3 0.0603 0.7505 0.016 0.004 0.980 0.000 0.000 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 3 0.3999 -0.1448 0.000 0.004 0.500 0.000 0.496 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 5E493E8F-3F91-4481-88E9-3A88F5F21BC1 5 0.3002 0.7958 0.048 0.004 0.100 0.000 0.848 0.000
#> A79C4685-5772-4BEE-8BBF-6F696BFCB3A4 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> BA3ED88C-6C87-4989-A23F-CD0C9644B66B 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 9980293D-AF0A-4215-9688-C576B1F8B519 3 0.2383 0.7466 0.024 0.096 0.880 0.000 0.000 0.000
#> AA3CC38B-D53A-49DA-86F7-792BD2E90159 1 0.0458 0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> 1E8A580C-F3D4-417D-BB42-DE825BB84D40 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 5B52F233-86AE-43EB-9848-797FAF19DC95 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> BFB9D106-9A1C-465C-81A0-58C27CAF5338 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 1D1CCCCA-5A5B-4139-BA62-7706D6163C20 3 0.0458 0.7443 0.000 0.016 0.984 0.000 0.000 0.000
#> DAFB5BBB-0BAA-427B-A856-148CC6F35980 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> 1D7483F7-F5D8-4F6C-8110-F383B63D01C9 5 0.0363 0.8872 0.000 0.000 0.012 0.000 0.988 0.000
#> 8E14902D-6783-4B7D-BB15-BA5136239FD4 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 9AAF18A7-28CC-4B46-BF45-223913E0CF70 1 0.0146 0.9421 0.996 0.000 0.004 0.000 0.000 0.000
#> AF08503F-B0E5-4C39-BA04-3823CEE0273E 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 654B538F-F998-439F-8B00-D5B9C3C470DC 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 0F901E0D-7B41-41AF-8947-ADDD64FE64F6 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> DF05AC80-ED12-4B68-84E7-45D5C80774C0 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> A5B70C7A-CC78-45ED-BC19-741012BC6E97 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 03A103AB-57BC-4C49-ADA9-FA58A6E5B636 1 0.3854 0.0534 0.536 0.000 0.464 0.000 0.000 0.000
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#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 6 0.2416 0.7192 0.156 0.000 0.000 0.000 0.000 0.844
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0146 0.9565 0.000 0.996 0.004 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 1 0.0458 0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 5 0.0363 0.8860 0.012 0.000 0.000 0.000 0.988 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.3797 0.3875 0.420 0.000 0.580 0.000 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 5 0.4097 0.7054 0.128 0.004 0.108 0.000 0.760 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.0291 0.7448 0.004 0.004 0.992 0.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 5 0.0260 0.8891 0.008 0.000 0.000 0.000 0.992 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 3 0.0632 0.7439 0.000 0.024 0.976 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 6 0.2135 0.7501 0.128 0.000 0.000 0.000 0.000 0.872
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.2092 0.8235 0.876 0.000 0.000 0.000 0.000 0.124
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.2378 0.8406 0.000 0.000 0.000 0.848 0.152 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.3076 0.6592 0.760 0.000 0.000 0.000 0.000 0.240
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.9825 0.000 0.000 0.000 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 5 0.0260 0.8891 0.008 0.000 0.000 0.000 0.992 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.0547 0.9302 0.980 0.000 0.000 0.000 0.020 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 6 0.3482 0.4712 0.000 0.000 0.000 0.316 0.000 0.684
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 6 0.3918 0.6871 0.124 0.000 0.000 0.000 0.108 0.768
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0458 0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.3428 0.5191 0.696 0.000 0.304 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 3 0.4264 0.4366 0.352 0.028 0.620 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 5 0.6409 0.5117 0.184 0.140 0.108 0.000 0.568 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.2260 0.7986 0.860 0.000 0.000 0.000 0.140 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 6 0.0363 0.8603 0.000 0.000 0.000 0.000 0.012 0.988
#> E6446572-BFA9-4018-89B3-7E4519EBE072 6 0.3050 0.6228 0.236 0.000 0.000 0.000 0.000 0.764
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 6 0.0000 0.8678 0.000 0.000 0.000 0.000 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.1814 0.7688 0.100 0.000 0.900 0.000 0.000 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.0458 0.9340 0.984 0.000 0.016 0.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9567 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 5 0.0000 0.8934 0.000 0.000 0.000 0.000 1.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 6 0.3810 0.3085 0.428 0.000 0.000 0.000 0.000 0.572
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0000 0.9443 1.000 0.000 0.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 4.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.All the plots in panels can be made by individual functions and they are plotted later in this section.
select_partition_number() produces several plots showing different
statistics for choosing “optimized” k. There are following statistics:
k;k, the area increased is defined as \(A_k - A_{k-1}\).The detailed explanations of these statistics can be found in the cola vignette.
Generally speaking, lower PAC score, higher mean silhouette score or higher
concordance corresponds to better partition. Rand index and Jaccard index
measure how similar the current partition is compared to partition with k-1.
If they are too similar, we won't accept k is better than k-1.
select_partition_number(res)
The numeric values for all these statistics can be obtained by get_stats().
get_stats(res)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> 2 2 0.834 0.913 0.963 0.2971 0.709 0.709
#> 3 3 0.433 0.455 0.667 0.7237 0.665 0.549
#> 4 4 0.696 0.646 0.843 0.2761 0.753 0.498
#> 5 5 0.734 0.822 0.905 0.0414 0.865 0.643
#> 6 6 0.788 0.823 0.904 0.0940 0.862 0.610
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 4
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.9065 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.5629 0.8438 0.868 0.132
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 2 0.0672 0.9639 0.008 0.992
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.7376 0.7122 0.208 0.792
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.9701 0.000 1.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.9701 0.000 1.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.0000 0.9701 0.000 1.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.0000 0.9701 0.000 1.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 1 0.6343 0.8242 0.840 0.160
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.9065 1.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.8909 0.6423 0.692 0.308
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0000 0.9701 0.000 1.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.9701 0.000 1.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.9701 0.000 1.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.0938 0.9607 0.012 0.988
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.0000 0.9701 0.000 1.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 2 0.0376 0.9671 0.004 0.996
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.9701 0.000 1.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.7950 0.7393 0.760 0.240
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.9701 0.000 1.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 1 0.1184 0.9050 0.984 0.016
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.9701 0.000 1.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.9065 1.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.9701 0.000 1.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 2 0.0000 0.9701 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.9701 0.000 1.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.0000 0.9701 0.000 1.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.0000 0.9701 0.000 1.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.0376 0.9671 0.004 0.996
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 2 0.0938 0.9607 0.012 0.988
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.0000 0.9701 0.000 1.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.9701 0.000 1.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 2 0.2236 0.9372 0.036 0.964
#> C06D8112-0FA0-4607-988D-589D8694743F 2 0.0000 0.9701 0.000 1.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.0000 0.9701 0.000 1.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.0376 0.9671 0.004 0.996
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.0000 0.9701 0.000 1.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 2 0.0000 0.9701 0.000 1.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 2 0.9491 0.3689 0.368 0.632
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 2 0.9323 0.4225 0.348 0.652
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 2 0.0000 0.9701 0.000 1.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.0000 0.9701 0.000 1.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.9701 0.000 1.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.9065 1.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.0000 0.9701 0.000 1.000
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#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.0000 0.9701 0.000 1.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 2 0.0000 0.9701 0.000 1.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 2 0.0000 0.9701 0.000 1.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 2 0.0000 0.9701 0.000 1.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0000 0.9701 0.000 1.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0000 0.9701 0.000 1.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 2 0.0000 0.9701 0.000 1.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 2 0.0000 0.9701 0.000 1.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.8081 0.7278 0.752 0.248
#> 887E7408-C7D7-420F-A763-0EE70A316D17 2 0.0000 0.9701 0.000 1.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0000 0.9701 0.000 1.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0000 0.9701 0.000 1.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 2 0.0000 0.9701 0.000 1.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 2 0.0000 0.9701 0.000 1.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 2 0.0000 0.9701 0.000 1.000
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.0938 0.9607 0.012 0.988
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.0000 0.9701 0.000 1.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.0938 0.9607 0.012 0.988
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.0000 0.9701 0.000 1.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0000 0.9701 0.000 1.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 2 0.0000 0.9701 0.000 1.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 2 0.0000 0.9701 0.000 1.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 2 0.0000 0.9701 0.000 1.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0938 0.9607 0.012 0.988
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.7056 0.7380 0.192 0.808
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 2 0.8016 0.6458 0.244 0.756
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0376 0.9671 0.004 0.996
#> B23A1419-0406-48BF-813B-B6ED6FD98789 2 0.0000 0.9701 0.000 1.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.9661 0.4691 0.608 0.392
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.9701 0.000 1.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 2 0.0000 0.9701 0.000 1.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.0000 0.9701 0.000 1.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.0000 0.9701 0.000 1.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 2 0.0000 0.9701 0.000 1.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 2 0.0000 0.9701 0.000 1.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.9065 1.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 2 0.4939 0.8556 0.108 0.892
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 2 0.7056 0.7381 0.192 0.808
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 2 0.0000 0.9701 0.000 1.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.8813 0.6553 0.700 0.300
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 2 0.0000 0.9701 0.000 1.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 2 0.0000 0.9701 0.000 1.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.0000 0.9701 0.000 1.000
#> 1122039D-5785-4F70-9916-17C585453512 1 0.1184 0.9050 0.984 0.016
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.9065 1.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.0672 0.9640 0.008 0.992
#> C56C7ED7-A684-40CC-B426-B108E2248467 1 0.1184 0.9050 0.984 0.016
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0000 0.9701 0.000 1.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.0000 0.9701 0.000 1.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.0000 0.9701 0.000 1.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 1 0.0938 0.9053 0.988 0.012
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 2 0.0376 0.9670 0.004 0.996
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 2 0.0000 0.9701 0.000 1.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 2 0.0000 0.9701 0.000 1.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.0000 0.9701 0.000 1.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0376 0.9671 0.004 0.996
#> 1B73CE27-B464-41E6-BE27-90FA13683331 2 0.0000 0.9701 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.4815 0.8625 0.104 0.896
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.0000 0.9701 0.000 1.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.0000 0.9701 0.000 1.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.9988 -0.0768 0.480 0.520
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0000 0.9701 0.000 1.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.9701 0.000 1.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 2 0.0938 0.9607 0.012 0.988
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 2 0.1184 0.9576 0.016 0.984
#> EB7883EB-0079-4548-9132-169E94A698BA 2 0.0000 0.9701 0.000 1.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 2 0.0000 0.9701 0.000 1.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 2 0.0000 0.9701 0.000 1.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 2 0.0000 0.9701 0.000 1.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.0938 0.9606 0.012 0.988
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 1 0.2043 0.8985 0.968 0.032
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.9701 0.000 1.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.0938 0.9607 0.012 0.988
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 2 0.0000 0.9701 0.000 1.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 2 0.0000 0.9701 0.000 1.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.0000 0.9701 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.79853 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.6676 -0.29094 0.476 0.008 0.516
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3116 0.48767 0.108 0.000 0.892
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.2537 0.52648 0.080 0.000 0.920
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.6295 0.64372 0.000 0.528 0.472
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.6305 0.63924 0.000 0.516 0.484
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.6302 0.64202 0.000 0.520 0.480
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 2 0.6307 0.63270 0.000 0.512 0.488
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.6944 -0.28860 0.468 0.016 0.516
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.79853 1.000 0.000 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 1 0.5785 0.51101 0.668 0.332 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.6299 0.64329 0.000 0.524 0.476
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0237 0.45732 0.004 0.996 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.6295 0.64372 0.000 0.528 0.472
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.6941 0.63751 0.016 0.520 0.464
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 2 0.6299 0.64329 0.000 0.524 0.476
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.0237 0.55028 0.000 0.004 0.996
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0237 0.45732 0.004 0.996 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 1 0.5465 0.56111 0.712 0.288 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0237 0.45732 0.004 0.996 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.6944 -0.28860 0.468 0.016 0.516
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0237 0.45732 0.004 0.996 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 1 0.0000 0.79853 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0237 0.45732 0.004 0.996 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.5016 0.27331 0.000 0.240 0.760
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0475 0.45318 0.004 0.992 0.004
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 2 0.6305 0.63924 0.000 0.516 0.484
#> EE97212E-8D5D-4548-8DD2-317049601FDB 2 0.6299 0.64329 0.000 0.524 0.476
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 2 0.6295 0.64372 0.000 0.528 0.472
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 2 0.6813 0.64023 0.012 0.520 0.468
#> 97C34F1F-2002-4771-8D99-511EA08591CD 2 0.6307 0.63279 0.000 0.512 0.488
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0237 0.45732 0.004 0.996 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.2537 0.52652 0.080 0.000 0.920
#> C06D8112-0FA0-4607-988D-589D8694743F 2 0.6305 0.63924 0.000 0.516 0.484
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 2 0.6295 0.64372 0.000 0.528 0.472
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 2 0.6509 0.64350 0.004 0.524 0.472
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 2 0.6295 0.64372 0.000 0.528 0.472
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.5722 0.09521 0.004 0.292 0.704
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.6252 -0.23260 0.444 0.000 0.556
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.6026 -0.09376 0.376 0.000 0.624
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.6309 -0.60310 0.000 0.496 0.504
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 2 0.6305 0.63924 0.000 0.516 0.484
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0237 0.45732 0.004 0.996 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 1 0.0000 0.79853 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 2 0.6305 0.63924 0.000 0.516 0.484
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 2 0.6509 0.64278 0.004 0.524 0.472
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.6944 -0.28860 0.468 0.016 0.516
#> 066B10C1-777F-4863-ACCA-6684310B913E 2 0.6509 0.64350 0.004 0.524 0.472
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 1 0.4291 0.66696 0.820 0.180 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0747 0.45427 0.016 0.984 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 2 0.6305 0.63924 0.000 0.516 0.484
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.4346 0.39829 0.000 0.184 0.816
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 1 0.6905 0.38585 0.544 0.016 0.440
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 2 0.6305 0.63924 0.000 0.516 0.484
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.4002 0.43249 0.000 0.160 0.840
#> 311D089C-33F1-4722-9118-F56427C5C128 2 0.9199 0.48306 0.168 0.504 0.328
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0237 0.45732 0.004 0.996 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 2 0.6291 0.64319 0.000 0.532 0.468
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 2 0.6295 0.64372 0.000 0.528 0.472
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0475 0.45866 0.004 0.992 0.004
#> A77DDA16-167D-4444-8C58-526C99F2B406 2 0.6299 0.64329 0.000 0.524 0.476
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0829 0.46090 0.004 0.984 0.012
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 2 0.6302 0.64202 0.000 0.520 0.480
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 2 0.6672 0.64214 0.008 0.520 0.472
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.6192 0.34009 0.580 0.420 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 1 0.6235 0.28423 0.564 0.436 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 1 0.0000 0.79853 1.000 0.000 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 2 0.9338 0.45438 0.196 0.504 0.300
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 3 0.5591 0.04927 0.000 0.304 0.696
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.4291 0.40673 0.000 0.180 0.820
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.6944 -0.28860 0.468 0.016 0.516
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 1 0.0000 0.79853 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.3851 0.49035 0.004 0.860 0.136
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.6944 -0.28860 0.468 0.016 0.516
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 2 0.6299 0.64345 0.000 0.524 0.476
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.2261 0.54041 0.068 0.000 0.932
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.6944 -0.28860 0.468 0.016 0.516
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 2 0.7278 0.62992 0.028 0.516 0.456
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.5882 -0.14867 0.000 0.348 0.652
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0237 0.45732 0.004 0.996 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 2 0.6305 0.63924 0.000 0.516 0.484
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.6126 -0.23069 0.000 0.400 0.600
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 2 0.6295 0.64372 0.000 0.528 0.472
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 1 0.9386 0.30476 0.500 0.296 0.204
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 2 0.6305 0.63924 0.000 0.516 0.484
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1411 0.46741 0.000 0.964 0.036
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 3 0.6204 -0.41135 0.000 0.424 0.576
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.4094 0.51382 0.028 0.100 0.872
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 3 0.6305 -0.57544 0.000 0.484 0.516
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.6260 0.63359 0.000 0.552 0.448
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 3 0.4974 0.28316 0.000 0.236 0.764
#> 4D361EA8-1F79-4B89-841B-87F83215D805 2 0.6305 0.63924 0.000 0.516 0.484
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 2 0.6669 0.64226 0.008 0.524 0.468
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0237 0.45732 0.004 0.996 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 2 0.6305 0.63924 0.000 0.516 0.484
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 1 0.0000 0.79853 1.000 0.000 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.6460 0.62681 0.004 0.556 0.440
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.1289 0.45031 0.032 0.968 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.2796 0.51042 0.092 0.000 0.908
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0237 0.45732 0.004 0.996 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 3 0.6045 -0.26381 0.000 0.380 0.620
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#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0237 0.45732 0.004 0.996 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 2 0.6302 0.64202 0.000 0.520 0.480
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 1 0.6308 0.11875 0.508 0.492 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0475 0.45866 0.004 0.992 0.004
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 2 0.6305 0.63924 0.000 0.516 0.484
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.6305 0.63924 0.000 0.516 0.484
#> 5E03E52F-957D-455B-A007-19714FAA818A 2 0.6305 0.63924 0.000 0.516 0.484
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.6295 -0.54513 0.000 0.472 0.528
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.5722 0.09473 0.004 0.292 0.704
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.79853 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.1860 0.55219 0.052 0.000 0.948
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.1860 0.55219 0.052 0.000 0.948
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.6244 -0.45863 0.000 0.440 0.560
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.5650 0.53379 0.688 0.312 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 2 0.6305 0.63924 0.000 0.516 0.484
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.0237 0.55028 0.000 0.004 0.996
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 2 0.6305 0.63924 0.000 0.516 0.484
#> 1122039D-5785-4F70-9916-17C585453512 3 0.6813 -0.28419 0.468 0.012 0.520
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.79853 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.6509 0.64350 0.004 0.524 0.472
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.6944 -0.28860 0.468 0.016 0.516
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.6669 0.64048 0.008 0.524 0.468
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.4178 0.41554 0.000 0.172 0.828
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 2 0.6305 0.63924 0.000 0.516 0.484
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.6944 -0.28860 0.468 0.016 0.516
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.0892 0.54632 0.000 0.020 0.980
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 2 0.6305 0.63924 0.000 0.516 0.484
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.0237 0.55028 0.000 0.004 0.996
#> 79BA86D9-466F-48D7-B64B-F933B6995716 2 0.6305 0.63924 0.000 0.516 0.484
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.3644 0.49153 0.004 0.872 0.124
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.4452 0.38657 0.000 0.192 0.808
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5678 0.21741 0.316 0.684 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 2 0.6305 0.63924 0.000 0.516 0.484
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.6305 0.63924 0.000 0.516 0.484
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 2 0.8427 0.19189 0.412 0.500 0.088
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.6295 0.64372 0.000 0.528 0.472
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0237 0.45732 0.004 0.996 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 2 0.6813 0.64023 0.012 0.520 0.468
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 2 0.6941 0.63751 0.016 0.520 0.464
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.5621 0.04583 0.000 0.308 0.692
#> E6446572-BFA9-4018-89B3-7E4519EBE072 2 0.6307 0.63270 0.000 0.512 0.488
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.4750 0.33772 0.000 0.216 0.784
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 2 0.6305 0.63924 0.000 0.516 0.484
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.7517 -0.24367 0.420 0.040 0.540
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.6944 -0.28860 0.468 0.016 0.516
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0237 0.45732 0.004 0.996 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.6672 0.64214 0.008 0.520 0.472
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.5138 0.23241 0.000 0.252 0.748
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0424 0.54962 0.000 0.008 0.992
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.6302 0.64202 0.000 0.520 0.480
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.0336 0.51963 0.000 0.000 0.992 0.008
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.4994 0.40296 0.480 0.000 0.520 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.4994 0.40296 0.480 0.000 0.520 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.6894 0.75904 0.512 0.112 0.376 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.5165 0.87733 0.512 0.004 0.484 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 4 0.4996 0.00946 0.000 0.484 0.000 0.516
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.5404 0.87349 0.512 0.012 0.476 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.5292 0.87579 0.512 0.008 0.480 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.6521 0.80519 0.512 0.076 0.412 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.5165 0.87725 0.512 0.004 0.484 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.1389 0.54031 0.048 0.000 0.952 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.4500 0.48679 0.000 0.316 0.000 0.684
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 3 0.4998 -0.84666 0.488 0.000 0.512 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.5165 0.87733 0.512 0.004 0.484 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.5404 0.87360 0.512 0.012 0.476 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.5332 0.87594 0.512 0.004 0.480 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.4994 0.40296 0.480 0.000 0.520 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.5506 0.87058 0.512 0.016 0.472 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.5688 0.86418 0.512 0.024 0.464 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5771 0.86061 0.512 0.028 0.460 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.0707 0.52938 0.020 0.000 0.980 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.4994 0.40296 0.480 0.000 0.520 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 3 0.5000 -0.85893 0.496 0.000 0.504 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.7063 0.73016 0.508 0.132 0.360 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.5292 0.87581 0.512 0.008 0.480 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.1637 0.42092 0.060 0.000 0.940 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 3 0.1118 0.46522 0.036 0.000 0.964 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.8367 0.64508 0.512 0.072 0.280 0.136
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.7380 0.63739 0.512 0.200 0.288 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.5404 0.87360 0.512 0.012 0.476 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.5165 0.87733 0.512 0.004 0.484 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.5165 0.87733 0.512 0.004 0.484 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.5600 0.86739 0.512 0.020 0.468 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 4 0.7467 -0.15201 0.372 0.004 0.156 0.468
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.6698 0.34395 0.156 0.004 0.208 0.632
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.7133 0.44509 0.512 0.344 0.144 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 3 0.0817 0.48550 0.024 0.000 0.976 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.7053 0.73131 0.512 0.132 0.356 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.4972 0.41689 0.456 0.000 0.544 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.4996 0.39920 0.484 0.000 0.516 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.6366 0.22743 0.512 0.424 0.064 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.1302 0.53860 0.044 0.000 0.956 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.4992 -0.16597 0.000 0.476 0.524 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.5404 0.87360 0.512 0.012 0.476 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 2 0.7269 0.25242 0.008 0.480 0.396 0.116
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.1211 0.85568 0.040 0.960 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.5158 0.40586 0.472 0.004 0.524 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4431 0.52225 0.304 0.696 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.4999 0.87379 0.508 0.000 0.492 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.7380 0.51829 0.512 0.288 0.200 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.2611 0.78114 0.096 0.896 0.008 0.000
#> 31322670-76A2-4308-A71F-D8E00049519D 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 3 0.2081 0.55062 0.084 0.000 0.916 0.000
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 3 0.3024 0.18933 0.148 0.000 0.852 0.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.6366 0.22744 0.512 0.424 0.064 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 2 0.2408 0.79914 0.000 0.896 0.104 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 3 0.4967 0.41873 0.452 0.000 0.548 0.000
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.4103 0.59477 0.000 0.744 0.000 0.256
#> C44C898C-EEF9-4E03-911A-9D951312C380 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 1 0.5292 0.87581 0.512 0.008 0.480 0.000
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.6192 0.18683 0.512 0.436 0.052 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.0000 0.89542 0.000 1.000 0.000 0.000
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#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.5506 0.87058 0.512 0.016 0.472 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0469 0.88594 0.000 0.988 0.012 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.2408 0.31915 0.104 0.000 0.896 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.4999 -0.85312 0.492 0.000 0.508 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.4998 -0.00686 0.512 0.488 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.4994 0.40296 0.480 0.000 0.520 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.7861 0.52736 0.508 0.268 0.208 0.016
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.5292 0.87581 0.512 0.008 0.480 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 4 0.4998 -0.00604 0.000 0.488 0.000 0.512
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.1211 0.45867 0.040 0.000 0.960 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 4 0.4855 0.28421 0.000 0.400 0.000 0.600
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 1122039D-5785-4F70-9916-17C585453512 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.90667 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.5771 0.86008 0.512 0.028 0.460 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.6822 0.34587 0.512 0.384 0.104 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.0188 0.52166 0.004 0.000 0.996 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1940 0.54883 0.076 0.000 0.924 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.4998 -0.00686 0.512 0.488 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.4996 -0.84001 0.484 0.000 0.516 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5600 0.12459 0.468 0.512 0.000 0.020
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.5165 0.87733 0.512 0.004 0.484 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.8640 0.39334 0.512 0.232 0.092 0.164
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.5850 0.85636 0.512 0.032 0.456 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.5600 0.86739 0.512 0.020 0.468 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.5766 0.86507 0.512 0.020 0.464 0.004
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.4776 -0.61950 0.376 0.000 0.624 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.0188 0.51397 0.004 0.000 0.996 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4998 0.87825 0.512 0.000 0.488 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4996 0.39928 0.484 0.000 0.516 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.4998 0.39603 0.488 0.000 0.512 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.89542 0.000 1.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5292 0.87581 0.512 0.008 0.480 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.4981 -0.80709 0.464 0.000 0.536 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0000 0.51925 0.000 0.000 1.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.5292 0.87581 0.512 0.008 0.480 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0162 0.9393 0.000 0.000 0.000 0.004 0.996
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.4221 0.7252 0.108 0.000 0.780 0.000 0.112
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.3346 0.7594 0.036 0.008 0.848 0.108 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.3216 0.7705 0.044 0.000 0.848 0.108 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.1661 0.8830 0.940 0.036 0.024 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.2690 0.6850 0.000 0.000 0.844 0.156 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.1638 0.9101 0.000 0.000 0.064 0.004 0.932
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.3768 0.7623 0.020 0.808 0.156 0.000 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0324 0.9049 0.992 0.004 0.004 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0609 0.8999 0.980 0.020 0.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 1 0.3123 0.8072 0.828 0.012 0.160 0.000 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.0912 0.8983 0.972 0.012 0.016 0.000 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.2648 0.8426 0.152 0.000 0.848 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0162 0.8915 0.000 0.996 0.004 0.000 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.4214 0.7382 0.000 0.780 0.152 0.004 0.064
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 5 0.0880 0.9358 0.000 0.000 0.032 0.000 0.968
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0510 0.9017 0.984 0.000 0.016 0.000 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0566 0.8983 0.012 0.984 0.004 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0162 0.9056 0.996 0.004 0.000 0.000 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.1197 0.8896 0.952 0.000 0.048 0.000 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.2470 0.8500 0.884 0.012 0.104 0.000 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.0162 0.9052 0.996 0.000 0.004 0.000 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.3216 0.7705 0.044 0.000 0.848 0.108 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 1 0.1670 0.8825 0.936 0.012 0.052 0.000 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.1732 0.8734 0.920 0.000 0.080 0.000 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.0955 0.8948 0.968 0.028 0.004 0.000 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.2605 0.8424 0.148 0.000 0.852 0.000 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.2690 0.8418 0.156 0.000 0.844 0.000 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.3267 0.7685 0.044 0.000 0.844 0.112 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 5 0.0000 0.9402 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 1 0.4589 0.6278 0.704 0.048 0.248 0.000 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 1 0.2522 0.8482 0.880 0.012 0.108 0.000 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.6075 0.3928 0.216 0.012 0.160 0.000 0.612
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.2561 0.8013 0.000 0.856 0.144 0.000 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.3913 0.4119 0.676 0.000 0.324 0.000 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.0162 0.9057 0.996 0.004 0.000 0.000 0.000
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 1 0.0510 0.9017 0.984 0.000 0.016 0.000 0.000
#> 311D089C-33F1-4722-9118-F56427C5C128 1 0.3264 0.8021 0.820 0.016 0.164 0.000 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.1444 0.8853 0.948 0.040 0.012 0.000 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 1 0.0290 0.9046 0.992 0.008 0.000 0.000 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.1410 0.8593 0.060 0.940 0.000 0.000 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.2522 0.8439 0.880 0.012 0.108 0.000 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 1 0.5223 0.6902 0.708 0.012 0.172 0.000 0.108
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 3 0.6889 0.1060 0.344 0.012 0.436 0.000 0.208
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 5 0.1041 0.9355 0.000 0.000 0.032 0.004 0.964
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 1 0.3224 0.8043 0.824 0.016 0.160 0.000 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 1 0.3424 0.6113 0.760 0.000 0.240 0.000 0.000
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 5 0.0794 0.9368 0.000 0.000 0.028 0.000 0.972
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 2 0.0898 0.8939 0.020 0.972 0.008 0.000 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.1704 0.8687 0.928 0.068 0.004 0.000 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 3 0.3297 0.7962 0.068 0.000 0.848 0.084 0.000
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2648 0.6883 0.000 0.000 0.848 0.152 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 1 0.3264 0.8021 0.820 0.016 0.164 0.000 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.4179 0.7644 0.152 0.072 0.776 0.000 0.000
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 2 0.0566 0.8987 0.012 0.984 0.004 0.000 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 2 0.5091 0.3178 0.044 0.584 0.372 0.000 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.0324 0.9049 0.992 0.004 0.004 0.000 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.4037 0.4326 0.000 0.188 0.776 0.008 0.028
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 46351E5C-2438-4B6A-8343-DDF329086771 2 0.2929 0.7015 0.180 0.820 0.000 0.000 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.3319 0.7397 0.040 0.100 0.852 0.008 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 2 0.4425 0.1744 0.452 0.544 0.004 0.000 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.3183 0.8076 0.828 0.016 0.156 0.000 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 5 0.1124 0.9339 0.000 0.000 0.036 0.004 0.960
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#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.3368 0.8013 0.820 0.024 0.156 0.000 0.000
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 5 0.0000 0.9402 0.000 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.2424 0.8125 0.000 0.868 0.132 0.000 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.0162 0.9055 0.996 0.000 0.004 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 1 0.0865 0.8970 0.972 0.024 0.004 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 1 0.0865 0.8969 0.972 0.024 0.004 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 1 0.0865 0.8978 0.972 0.024 0.004 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 1 0.6103 0.4010 0.548 0.292 0.160 0.000 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 1 0.2006 0.8698 0.916 0.012 0.072 0.000 0.000
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.4482 0.4367 0.000 0.636 0.348 0.016 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.3492 0.8140 0.188 0.016 0.796 0.000 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.2648 0.8426 0.152 0.000 0.848 0.000 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 1 0.0324 0.9049 0.992 0.004 0.004 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.3237 0.7752 0.048 0.000 0.848 0.104 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 5 0.0000 0.9402 0.000 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.4718 0.1718 0.444 0.540 0.016 0.000 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.2690 0.8418 0.156 0.000 0.844 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.2605 0.7728 0.852 0.000 0.148 0.000 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.2179 0.7970 0.112 0.888 0.000 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.3109 0.8108 0.200 0.000 0.800 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.6595 0.1722 0.456 0.012 0.384 0.000 0.148
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.3143 0.8055 0.204 0.000 0.796 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.4300 -0.1926 0.524 0.000 0.476 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0290 0.9037 0.992 0.000 0.008 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.2966 0.8246 0.848 0.016 0.136 0.000 0.000
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.3584 0.7947 0.064 0.020 0.848 0.068 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.3224 0.8043 0.824 0.016 0.160 0.000 0.000
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 1 0.2305 0.8585 0.896 0.012 0.092 0.000 0.000
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0912 0.8954 0.012 0.972 0.016 0.000 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.1965 0.8331 0.904 0.000 0.096 0.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.2516 0.7766 0.860 0.000 0.140 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 1 0.4648 0.7214 0.740 0.104 0.156 0.000 0.000
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.3216 0.7705 0.044 0.000 0.848 0.108 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.3304 0.7999 0.816 0.016 0.168 0.000 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.0963 0.8779 0.000 0.964 0.036 0.000 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 1 0.0162 0.9055 0.996 0.000 0.004 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.2690 0.7913 0.000 0.844 0.156 0.000 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.3274 0.7873 0.220 0.000 0.780 0.000 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 5 0.1041 0.9355 0.000 0.000 0.032 0.004 0.964
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.2690 0.8418 0.156 0.000 0.844 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.2690 0.8418 0.156 0.000 0.844 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.3278 0.7769 0.000 0.824 0.156 0.000 0.020
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.3796 0.6789 0.300 0.000 0.700 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0162 0.9052 0.996 0.000 0.004 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 4 0.0609 0.9235 0.000 0.000 0.020 0.980 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 5 0.0000 0.9402 0.000 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.2612 0.8377 0.868 0.008 0.124 0.000 0.000
#> C56C7ED7-A684-40CC-B426-B108E2248467 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 1 0.5273 0.6372 0.680 0.160 0.160 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.2886 0.8409 0.148 0.008 0.844 0.000 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0290 0.9049 0.992 0.000 0.008 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.4015 0.3384 0.652 0.000 0.348 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.0693 0.9002 0.980 0.012 0.008 0.000 0.000
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.2648 0.8426 0.152 0.000 0.848 0.000 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 1 0.6031 0.2712 0.520 0.352 0.128 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0162 0.9052 0.996 0.000 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.2690 0.7913 0.000 0.844 0.156 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.3264 0.8021 0.820 0.016 0.164 0.000 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.0912 0.9005 0.972 0.016 0.012 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.2864 0.8270 0.852 0.012 0.136 0.000 0.000
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.2864 0.8270 0.852 0.012 0.136 0.000 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.3395 0.6170 0.764 0.000 0.236 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0290 0.9043 0.992 0.000 0.008 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.2690 0.8420 0.156 0.000 0.844 0.000 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0000 0.9062 1.000 0.000 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.4901 0.5398 0.000 0.096 0.708 0.196 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 4 0.0000 0.9408 0.000 0.000 0.000 1.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0404 0.8998 0.012 0.988 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.2723 0.8362 0.864 0.012 0.124 0.000 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0794 0.8924 0.972 0.000 0.028 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.2648 0.8426 0.152 0.000 0.848 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0162 0.9055 0.996 0.000 0.004 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 6 0.1075 0.93428 0.000 0.000 0.000 0.000 0.048 0.952
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.2532 0.81546 0.012 0.000 0.884 0.000 0.024 0.080
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.1088 0.85223 0.000 0.000 0.960 0.016 0.024 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.1176 0.84880 0.000 0.000 0.956 0.020 0.024 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.0508 0.91434 0.984 0.000 0.012 0.000 0.004 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.2176 0.81083 0.000 0.000 0.896 0.080 0.024 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 6 0.1663 0.92518 0.000 0.000 0.000 0.000 0.088 0.912
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.1461 0.64185 0.000 0.044 0.000 0.000 0.940 0.016
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 5 0.3023 0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 5 0.4150 0.65878 0.320 0.000 0.028 0.000 0.652 0.000
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 3 0.0405 0.86312 0.004 0.000 0.988 0.000 0.008 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.0713 0.88715 0.000 0.972 0.000 0.000 0.028 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 5 0.1498 0.63355 0.000 0.032 0.000 0.000 0.940 0.028
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 4 0.0000 0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 6 0.0000 0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.1633 0.90030 0.932 0.000 0.044 0.000 0.024 0.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> EE97212E-8D5D-4548-8DD2-317049601FDB 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 1 0.0937 0.89408 0.960 0.000 0.000 0.000 0.040 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 5 0.2941 0.80719 0.220 0.000 0.000 0.000 0.780 0.000
#> 97C34F1F-2002-4771-8D99-511EA08591CD 1 0.1528 0.90187 0.936 0.000 0.048 0.000 0.016 0.000
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 3 0.1341 0.84212 0.000 0.000 0.948 0.028 0.024 0.000
#> C06D8112-0FA0-4607-988D-589D8694743F 1 0.0713 0.91312 0.972 0.000 0.028 0.000 0.000 0.000
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.3360 0.76346 0.264 0.000 0.004 0.000 0.732 0.000
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.2300 0.77784 0.856 0.000 0.000 0.000 0.144 0.000
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 3 0.0909 0.86139 0.012 0.000 0.968 0.000 0.020 0.000
#> A84EA172-9823-40E9-BC22-C882725DD1C8 3 0.0914 0.86160 0.016 0.000 0.968 0.000 0.016 0.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 3 0.0993 0.85531 0.000 0.000 0.964 0.012 0.024 0.000
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.0260 0.91170 0.992 0.000 0.000 0.000 0.008 0.000
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.0458 0.91426 0.984 0.000 0.016 0.000 0.000 0.000
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 6 0.0000 0.94292 0.000 0.000 0.000 0.000 0.000 1.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.0547 0.91397 0.980 0.000 0.020 0.000 0.000 0.000
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 5 0.4459 0.74499 0.204 0.004 0.084 0.000 0.708 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 4 0.0000 0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 5 0.2969 0.80674 0.224 0.000 0.000 0.000 0.776 0.000
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 5 0.3746 0.67356 0.048 0.000 0.000 0.000 0.760 0.192
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 5 0.3076 0.61475 0.000 0.240 0.000 0.000 0.760 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 1 0.0891 0.91274 0.968 0.000 0.024 0.000 0.008 0.000
#> 4379559E-E467-49BD-9673-40A486146A3B 3 0.2826 0.75370 0.128 0.000 0.844 0.000 0.028 0.000
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 4 0.0000 0.98007 0.000 0.000 0.000 1.000 0.000 0.000
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#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.3023 0.80488 0.232 0.000 0.000 0.000 0.768 0.000
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.3960 0.64769 0.176 0.000 0.752 0.000 0.072 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.1418 0.90805 0.944 0.000 0.024 0.000 0.032 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.1341 0.85573 0.028 0.000 0.948 0.000 0.024 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0713 0.91304 0.972 0.000 0.028 0.000 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.2401 0.81333 0.000 0.028 0.900 0.048 0.024 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 4 0.0000 0.98007 0.000 0.000 0.000 1.000 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.0000 0.90508 0.000 1.000 0.000 0.000 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.3371 0.46972 0.708 0.000 0.000 0.000 0.292 0.000
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.1950 0.88878 0.912 0.000 0.064 0.000 0.024 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0508 0.86272 0.004 0.000 0.984 0.000 0.012 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0458 0.90906 0.984 0.000 0.000 0.000 0.016 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.
Signature heatmaps where rows are scaled:
get_signatures(res, k = 2)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
get_signature() returns a data frame invisibly. TO get the list of signatures, the function
call should be assigned to a variable explicitly. In following code, if plot argument is set
to FALSE, no heatmap is plotted while only the differential analysis is performed.
# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)
An example of the output of tb is:
#> which_row fdr mean_1 mean_2 scaled_mean_1 scaled_mean_2 km
#> 1 38 0.042760348 8.373488 9.131774 -0.5533452 0.5164555 1
#> 2 40 0.018707592 7.106213 8.469186 -0.6173731 0.5762149 1
#> 3 55 0.019134737 10.221463 11.207825 -0.6159697 0.5749050 1
#> 4 59 0.006059896 5.921854 7.869574 -0.6899429 0.6439467 1
#> 5 60 0.018055526 8.928898 10.211722 -0.6204761 0.5791110 1
#> 6 98 0.009384629 15.714769 14.887706 0.6635654 -0.6193277 2
...
The columns in tb are:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.km: Row groups if k-means clustering is applied to rows.UMAP plot which shows how samples are separated.
dimension_reduction(res, k = 2, method = "UMAP")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
If matrix rows can be associated to genes, consider to use functional_enrichment(res,
...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.
The object with results only for a single top-value method and a single partition method can be extracted as:
res = res_list["ATC", "NMF"]
# you can also extract it by
# res = res_list["ATC:NMF"]
A summary of res and all the functions that can be applied to it:
res
#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#> On a matrix with 17541 rows and 500 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.939 0.951 0.979 0.3497 0.663 0.663
#> 3 3 0.678 0.817 0.903 0.7815 0.634 0.478
#> 4 4 0.712 0.776 0.897 0.1375 0.751 0.452
#> 5 5 0.694 0.703 0.854 0.0944 0.777 0.390
#> 6 6 0.643 0.558 0.755 0.0545 0.895 0.587
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.976 1.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 2 0.0000 0.978 0.000 1.000
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#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.3114 0.928 0.056 0.944
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.0000 0.978 0.000 1.000
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#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.3114 0.928 0.056 0.944
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#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.7219 0.757 0.200 0.800
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#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.0000 0.978 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 1 0.0000 0.91115 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 3 0.2625 0.88053 0.000 0.084 0.916
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#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 2 0.3879 0.75112 0.000 0.848 0.152
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.7202 0.70833 0.160 0.716 0.124
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 3 0.1964 0.91199 0.000 0.056 0.944
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 3 0.3116 0.86633 0.000 0.108 0.892
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 3 0.1163 0.92565 0.000 0.028 0.972
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 2 0.1289 0.82200 0.000 0.968 0.032
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 1 0.0000 0.91115 1.000 0.000 0.000
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#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 3 0.5216 0.66353 0.000 0.260 0.740
#> 985FEEC2-9737-4018-80DF-21A07AB47900 3 0.1643 0.91844 0.000 0.044 0.956
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 1 0.2651 0.88748 0.928 0.060 0.012
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 3 0.0592 0.92985 0.000 0.012 0.988
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 2 0.0892 0.83362 0.000 0.980 0.020
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 2 0.0000 0.82939 0.000 1.000 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 3 0.2261 0.89692 0.000 0.068 0.932
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 1 0.3038 0.85380 0.896 0.104 0.000
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 2 0.1031 0.83158 0.000 0.976 0.024
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 3 0.0237 0.93042 0.000 0.004 0.996
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 2 0.0592 0.83146 0.000 0.988 0.012
#> 457090A2-AE7F-4E68-85EA-032DE8411110 3 0.0983 0.92896 0.004 0.016 0.980
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 3 0.0747 0.92566 0.000 0.016 0.984
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 3 0.0237 0.93042 0.000 0.004 0.996
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.4033 0.78350 0.136 0.856 0.008
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 3 0.0237 0.92990 0.000 0.004 0.996
#> 34ED910C-7470-4552-8561-D01D59190521 1 0.0000 0.91115 1.000 0.000 0.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.2496 0.82845 0.004 0.928 0.068
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 2 0.6192 0.25916 0.000 0.580 0.420
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 1 0.0592 0.90792 0.988 0.012 0.000
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.4912 0.73922 0.196 0.796 0.008
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 3 0.0592 0.92702 0.000 0.012 0.988
#> A9195281-8CAE-45A8-8493-744E577907FA 1 0.2804 0.88643 0.924 0.060 0.016
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.5529 0.66073 0.000 0.704 0.296
#> E789661A-C027-405D-9F76-E6D52CE3018B 2 0.4178 0.78123 0.000 0.828 0.172
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 3 0.0592 0.92985 0.000 0.012 0.988
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 2 0.0237 0.82841 0.004 0.996 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 3 0.0000 0.92994 0.000 0.000 1.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 3 0.0237 0.92990 0.000 0.004 0.996
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 3 0.1411 0.92236 0.000 0.036 0.964
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 3 0.1529 0.92054 0.000 0.040 0.960
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.5988 0.54473 0.000 0.632 0.368
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 2 0.6079 0.46275 0.000 0.612 0.388
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 1 0.0000 0.91115 1.000 0.000 0.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 2 0.0747 0.83345 0.000 0.984 0.016
#> 80936433-AA91-4219-98F1-706C36298060 2 0.1129 0.83364 0.004 0.976 0.020
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 3 0.0592 0.92702 0.000 0.012 0.988
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.8269 0.48734 0.316 0.584 0.100
#> D85CB054-7F54-4383-96C0-6C99761B84E7 3 0.1163 0.92565 0.000 0.028 0.972
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 1 0.0000 0.91115 1.000 0.000 0.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 2 0.1411 0.82025 0.000 0.964 0.036
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 3 0.1989 0.91479 0.004 0.048 0.948
#> 17CA5D73-4384-4645-83F8-587847043DD2 3 0.0237 0.93042 0.000 0.004 0.996
#> 40467950-A95C-4731-AD93-0A128442C837 1 0.0892 0.90347 0.980 0.000 0.020
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 3 0.2796 0.88260 0.000 0.092 0.908
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 3 0.1411 0.92236 0.000 0.036 0.964
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 3 0.0747 0.92566 0.000 0.016 0.984
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 3 0.1529 0.91357 0.000 0.040 0.960
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 3 0.1529 0.91384 0.000 0.040 0.960
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 1 0.6813 0.00331 0.520 0.468 0.012
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 1 0.0000 0.91115 1.000 0.000 0.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4605 0.73420 0.204 0.796 0.000
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 3 0.0424 0.93024 0.000 0.008 0.992
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 3 0.0237 0.92990 0.000 0.004 0.996
#> D957A2ED-97CD-4107-90A5-73C7691A5681 3 0.1964 0.91199 0.000 0.056 0.944
#> A7ECBC06-1332-4278-8723-85DC8351188A 3 0.6235 0.11296 0.000 0.436 0.564
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 3 0.0424 0.93062 0.000 0.008 0.992
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.5760 0.61137 0.000 0.672 0.328
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 3 0.0237 0.93042 0.000 0.004 0.996
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.5621 0.60966 0.308 0.692 0.000
#> 72DDC907-0901-4E61-83CF-38500D03FABC 3 0.6714 0.54195 0.296 0.032 0.672
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 2 0.1031 0.82486 0.000 0.976 0.024
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 2 0.4555 0.76230 0.000 0.800 0.200
#> E4F45B0B-91FA-49C0-9772-27321D23104B 3 0.1411 0.92236 0.000 0.036 0.964
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 2 0.3619 0.79909 0.000 0.864 0.136
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 3 0.1964 0.91199 0.000 0.056 0.944
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 3 0.5497 0.61371 0.000 0.292 0.708
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 1 0.0000 0.91115 1.000 0.000 0.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.2066 0.83040 0.000 0.940 0.060
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 3 0.0747 0.92594 0.000 0.016 0.984
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 3 0.0237 0.93042 0.000 0.004 0.996
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 3 0.6280 0.02798 0.000 0.460 0.540
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 2 0.0661 0.83054 0.004 0.988 0.008
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.4842 0.73237 0.000 0.776 0.224
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 3 0.0237 0.93042 0.000 0.004 0.996
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 3 0.0592 0.92702 0.000 0.012 0.988
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 1 0.0000 0.91115 1.000 0.000 0.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 3 0.0237 0.92990 0.000 0.004 0.996
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 2 0.0424 0.83096 0.000 0.992 0.008
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.0892 0.83362 0.000 0.980 0.020
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 3 0.0592 0.92702 0.000 0.012 0.988
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 3 0.0592 0.92702 0.000 0.012 0.988
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 3 0.0424 0.92862 0.000 0.008 0.992
#> EE40EE80-4520-4643-B906-48246BA616A7 1 0.2903 0.88591 0.924 0.048 0.028
#> C075F09E-623C-46ED-B927-889B48F450B3 2 0.6291 0.08339 0.000 0.532 0.468
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 1 0.2446 0.89126 0.936 0.052 0.012
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.9909 0.06264 0.364 0.368 0.268
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 2 0.0892 0.82849 0.000 0.980 0.020
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 3 0.0592 0.92702 0.000 0.012 0.988
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 3 0.1411 0.92236 0.000 0.036 0.964
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 3 0.0237 0.92990 0.000 0.004 0.996
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.6282 0.56971 0.324 0.664 0.012
#> 816CF68B-8476-4960-9F05-FB959A686323 2 0.4931 0.66429 0.000 0.768 0.232
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 1 0.1643 0.89804 0.956 0.044 0.000
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 2 0.4121 0.76492 0.168 0.832 0.000
#> B23A1419-0406-48BF-813B-B6ED6FD98789 3 0.1753 0.91609 0.000 0.048 0.952
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.5529 0.62860 0.296 0.704 0.000
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1860 0.83229 0.000 0.948 0.052
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 3 0.0237 0.93042 0.000 0.004 0.996
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 3 0.1529 0.92054 0.000 0.040 0.960
#> 5E03E52F-957D-455B-A007-19714FAA818A 3 0.0592 0.92985 0.000 0.012 0.988
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 3 0.0237 0.93042 0.000 0.004 0.996
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 3 0.2878 0.86852 0.000 0.096 0.904
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 1 0.0000 0.91115 1.000 0.000 0.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 3 0.0592 0.92702 0.000 0.012 0.988
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 3 0.0592 0.92702 0.000 0.012 0.988
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 3 0.0237 0.93042 0.000 0.004 0.996
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 1 0.3116 0.85197 0.892 0.108 0.000
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 3 0.0237 0.93042 0.000 0.004 0.996
#> C33059A9-A313-4806-B43B-0031365F3BE4 3 0.0592 0.92702 0.000 0.012 0.988
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 3 0.0424 0.93062 0.000 0.008 0.992
#> 1122039D-5785-4F70-9916-17C585453512 2 0.4974 0.65490 0.000 0.764 0.236
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 1 0.0000 0.91115 1.000 0.000 0.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 1 0.5276 0.78751 0.820 0.052 0.128
#> C56C7ED7-A684-40CC-B426-B108E2248467 2 0.1411 0.82025 0.000 0.964 0.036
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.5831 0.64075 0.284 0.708 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 2 0.4796 0.73799 0.000 0.780 0.220
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 3 0.0237 0.92990 0.000 0.004 0.996
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.1860 0.81368 0.000 0.948 0.052
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 3 0.0424 0.92862 0.000 0.008 0.992
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 3 0.0661 0.93016 0.004 0.008 0.988
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1289 0.91819 0.000 0.032 0.968
#> 79BA86D9-466F-48D7-B64B-F933B6995716 3 0.1411 0.92236 0.000 0.036 0.964
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.5884 0.65291 0.272 0.716 0.012
#> 1B73CE27-B464-41E6-BE27-90FA13683331 3 0.0000 0.92994 0.000 0.000 1.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.5529 0.62870 0.296 0.704 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 3 0.0237 0.93042 0.000 0.004 0.996
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 3 0.1753 0.91609 0.000 0.048 0.952
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 1 0.1860 0.89476 0.948 0.052 0.000
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.5859 0.58415 0.000 0.656 0.344
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.4195 0.78537 0.136 0.852 0.012
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.3039 0.88046 0.920 0.036 0.044
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 1 0.3028 0.87899 0.920 0.032 0.048
#> EB7883EB-0079-4548-9132-169E94A698BA 3 0.0000 0.92994 0.000 0.000 1.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 3 0.0237 0.93042 0.000 0.004 0.996
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 3 0.1643 0.91369 0.000 0.044 0.956
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 3 0.0237 0.93042 0.000 0.004 0.996
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 2 0.2066 0.81407 0.000 0.940 0.060
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 2 0.1753 0.81526 0.000 0.952 0.048
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2680 0.81746 0.068 0.924 0.008
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.5285 0.77305 0.812 0.040 0.148
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 3 0.0237 0.92990 0.000 0.004 0.996
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 3 0.0747 0.92566 0.000 0.016 0.984
#> 2785594A-571A-46B4-A901-CB9C62DC6174 3 0.1753 0.91609 0.000 0.048 0.952
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 1 0.3354 0.81138 0.880 0.020 0.016 0.084
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.2868 0.76106 0.136 0.000 0.864 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 3 0.4040 0.64358 0.248 0.000 0.752 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 2 0.0000 0.87320 0.000 1.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 2 0.3311 0.77106 0.172 0.828 0.000 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 2 0.1389 0.86088 0.048 0.952 0.000 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4040 0.65195 0.752 0.248 0.000 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0336 0.82861 0.008 0.000 0.992 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 2 0.4053 0.64636 0.000 0.768 0.004 0.228
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 2 0.0817 0.87026 0.024 0.976 0.000 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 2 0.0376 0.87231 0.000 0.992 0.004 0.004
#> 1C710173-532F-4435-BCE9-287AD8D247D9 2 0.0000 0.87320 0.000 1.000 0.000 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 2 0.2530 0.80338 0.000 0.888 0.000 0.112
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.6568 0.14700 0.512 0.408 0.000 0.080
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4781 0.39345 0.000 0.660 0.336 0.004
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 4 0.5085 0.57815 0.000 0.304 0.020 0.676
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.3837 0.64485 0.000 0.776 0.224 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.0469 0.82879 0.012 0.000 0.988 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.0376 0.87231 0.000 0.992 0.004 0.004
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 3 0.2973 0.78424 0.000 0.144 0.856 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 1 0.0188 0.89064 0.996 0.004 0.000 0.000
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#> 5E24404F-B1F2-43D8-A1BB-B94F799DBD63 3 0.1557 0.82744 0.000 0.056 0.944 0.000
#> 5F71B888-30B5-46CF-9A49-85F8AB7A0AFE 2 0.0188 0.87283 0.000 0.996 0.004 0.000
#> C77D7B0B-56B5-414A-BC5C-18E92E6BE886 4 0.3601 0.80675 0.056 0.000 0.084 0.860
#> 4326E7CF-426E-4352-9903-27BF06E76626 2 0.0188 0.87283 0.000 0.996 0.004 0.000
#> 3BB47EA2-169B-4109-973F-D7B3FA372F0D 1 0.4647 0.57335 0.704 0.008 0.000 0.288
#> E8DDAFD3-0B70-4B87-A243-0141696EE8CF 1 0.2345 0.82050 0.900 0.000 0.100 0.000
#> 985FEEC2-9737-4018-80DF-21A07AB47900 2 0.4331 0.61397 0.288 0.712 0.000 0.000
#> 244D5DA9-677F-46F6-BAC4-67EE32AC3291 2 0.0592 0.87203 0.000 0.984 0.000 0.016
#> F28A5BF1-DE90-468E-9192-AAA281AA618E 1 0.1302 0.87150 0.956 0.044 0.000 0.000
#> AE86FD13-75D2-4259-A607-12A1BA0CC513 3 0.4331 0.66932 0.000 0.288 0.712 0.000
#> E71AD72B-D55B-4654-89F7-C31CA32624F4 3 0.2011 0.81698 0.000 0.080 0.920 0.000
#> 7B86D69D-7C51-499A-A603-12D5541EEE96 1 0.0376 0.89042 0.992 0.004 0.004 0.000
#> 3E661E40-D5A5-49E0-9B16-0D6EB5AF65FB 4 0.3156 0.83930 0.000 0.068 0.048 0.884
#> 3FB923D7-F9BB-47A2-ADF6-8C6A48C8E765 3 0.3015 0.80135 0.024 0.092 0.884 0.000
#> 16E8C274-EA27-40FA-AEAE-C3EADD222400 1 0.0817 0.88388 0.976 0.024 0.000 0.000
#> 0420E91B-6FF9-4D0F-AAE8-73F3F38D33C9 3 0.0895 0.83190 0.004 0.020 0.976 0.000
#> 457090A2-AE7F-4E68-85EA-032DE8411110 1 0.2589 0.84700 0.912 0.044 0.000 0.044
#> CFDDDD40-6A3F-4460-B34E-8BCBD5716A99 1 0.0188 0.88976 0.996 0.004 0.000 0.000
#> 103E3A17-4FF4-4029-8723-DDEBFA6C2B5F 1 0.0592 0.88881 0.984 0.016 0.000 0.000
#> 754EB254-EE63-493D-9518-6DE9EE1C3D5B 2 0.1576 0.85124 0.000 0.948 0.048 0.004
#> A8CFE86F-B8B1-46EE-959D-391E3EEA1B4B 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> 34ED910C-7470-4552-8561-D01D59190521 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 5AECB107-F9E9-413C-AD1B-A777FB2D6982 2 0.0817 0.86532 0.000 0.976 0.024 0.000
#> 6A09CE3A-2558-4247-8D12-E4292C2BD18A 1 0.4134 0.61599 0.740 0.000 0.260 0.000
#> 80C54D0F-1525-4699-9AD7-E7D77BB34195 4 0.0895 0.90791 0.000 0.004 0.020 0.976
#> 36DC7E39-3EB0-46BA-9097-CE3275AB5F02 2 0.0524 0.87089 0.000 0.988 0.008 0.004
#> 8EF053CE-EBB7-4D2B-A0FD-112F86116E69 1 0.0188 0.88976 0.996 0.004 0.000 0.000
#> A9195281-8CAE-45A8-8493-744E577907FA 2 0.0469 0.87280 0.000 0.988 0.000 0.012
#> 24DC719A-9C27-4CC8-90D3-F33E5E944818 2 0.0336 0.87392 0.008 0.992 0.000 0.000
#> E789661A-C027-405D-9F76-E6D52CE3018B 3 0.7232 0.42479 0.164 0.320 0.516 0.000
#> 451FFA1C-4AA9-4830-A8D4-D51E1A5133D3 1 0.1940 0.84763 0.924 0.076 0.000 0.000
#> E466A9F5-E4CF-4A6F-9076-BF253B2C1E11 3 0.0188 0.82882 0.004 0.000 0.996 0.000
#> E803BBDE-80EB-45B2-AAEF-3FEBCE142345 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> CCABB592-8ED5-4879-9918-5C1CCF196A18 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> EFA5F15F-1C72-4476-BFA6-528C6D237CC4 1 0.4585 0.48586 0.668 0.332 0.000 0.000
#> A909220E-6FC9-49AC-9CFD-A76A4DF1C8B7 2 0.3074 0.78667 0.152 0.848 0.000 0.000
#> B57C849C-28B1-4315-885C-330B9C9482B3 2 0.7382 0.36046 0.220 0.520 0.260 0.000
#> 80105919-54FA-4BE7-8B88-D26AA563C6E7 1 0.4328 0.62886 0.748 0.008 0.244 0.000
#> 246D48D0-C61D-4F34-82B8-4079EE14FD17 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 14B4BE11-4576-4511-946E-28EB079ABA3E 3 0.3610 0.76296 0.000 0.200 0.800 0.000
#> 80936433-AA91-4219-98F1-706C36298060 3 0.4584 0.65573 0.000 0.300 0.696 0.004
#> A71D55E1-7DE3-4195-B181-CC10D0CE09C9 1 0.1042 0.88154 0.972 0.008 0.000 0.020
#> 241F589C-D559-43D7-8340-31EBCEB36E14 2 0.0000 0.87320 0.000 1.000 0.000 0.000
#> D85CB054-7F54-4383-96C0-6C99761B84E7 1 0.4522 0.51662 0.680 0.320 0.000 0.000
#> C2C08680-E96B-468D-BBFA-E7D7E0034249 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> D56B45D0-D99C-4D53-B71E-B1E8AC4787FE 3 0.0469 0.82879 0.012 0.000 0.988 0.000
#> 1D107D2C-0473-434D-AE4E-32F1FD4933C9 2 0.2589 0.81638 0.116 0.884 0.000 0.000
#> 17CA5D73-4384-4645-83F8-587847043DD2 1 0.0921 0.88148 0.972 0.028 0.000 0.000
#> 40467950-A95C-4731-AD93-0A128442C837 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> FE7B013B-9204-40BC-B644-7B3A5F170A96 2 0.0188 0.87357 0.004 0.996 0.000 0.000
#> 618FC260-3345-43CB-8CE0-93F55A01DBD1 1 0.4134 0.65078 0.740 0.260 0.000 0.000
#> DDC03CC8-8B62-4A23-BF0F-41A3A7FD7F65 1 0.0188 0.88902 0.996 0.000 0.004 0.000
#> F7C66216-32AD-49E8-AF01-C934896CCB5D 1 0.0707 0.88133 0.980 0.000 0.020 0.000
#> 90F0996F-AE69-4578-9B98-6572B5E708D4 1 0.0188 0.88855 0.996 0.000 0.004 0.000
#> 7AEAFD8C-31A0-4F4B-8381-23EDAAA3DC13 2 0.0188 0.87315 0.000 0.996 0.000 0.004
#> 8E08BD68-8325-4802-869F-BD7708EE7BAA 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 8A5CD6F1-AC5D-4EAC-A005-FCD66F8E7141 2 0.4220 0.61071 0.000 0.748 0.248 0.004
#> 65EFA716-D0C3-456C-AEFE-631B4130CD1B 1 0.2345 0.83107 0.900 0.100 0.000 0.000
#> 4032D247-79A3-4AC6-A3B6-51149B75DF0F 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> D957A2ED-97CD-4107-90A5-73C7691A5681 2 0.1474 0.85860 0.052 0.948 0.000 0.000
#> A7ECBC06-1332-4278-8723-85DC8351188A 2 0.0188 0.87349 0.004 0.996 0.000 0.000
#> 631F847D-1E4E-404F-A98D-F105DBD08CF6 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> D9364524-CD1F-4C45-A2EF-8CB401487001 2 0.0188 0.87361 0.004 0.996 0.000 0.000
#> 4BA56207-18D4-4C7A-A3E6-7834FA888DBA 1 0.0592 0.88777 0.984 0.016 0.000 0.000
#> A7D0A83A-4A51-4D8D-A66C-1EDC4B9F2291 2 0.0376 0.87231 0.000 0.992 0.004 0.004
#> 72DDC907-0901-4E61-83CF-38500D03FABC 4 0.6809 0.38491 0.332 0.116 0.000 0.552
#> 1E9BD546-C4B9-46C1-8A93-A90F2C38BA1E 3 0.0188 0.82882 0.004 0.000 0.996 0.000
#> 2D325CDD-7DE7-4058-B09E-632C14777E20 3 0.3428 0.75910 0.144 0.012 0.844 0.000
#> E4F45B0B-91FA-49C0-9772-27321D23104B 2 0.4916 0.29673 0.424 0.576 0.000 0.000
#> 7409A62F-0F0B-44AA-85BD-91B6C646E36F 3 0.4277 0.59969 0.280 0.000 0.720 0.000
#> BEF38FBC-DDAA-4B8E-91F1-A150452BB15C 2 0.1118 0.86602 0.036 0.964 0.000 0.000
#> 4287781B-8C52-4B61-9CF8-47A3FCC83201 1 0.3074 0.76810 0.848 0.000 0.152 0.000
#> D47CA3EF-BC7C-43D7-A006-26383200E0D1 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 1375359F-E6CF-4C08-88A7-CEA1E0B1765E 2 0.4500 0.48733 0.000 0.684 0.316 0.000
#> 8FE5A988-F803-436D-9A85-45E7DCEB8934 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> AC7DD1B2-EF04-435B-BC5E-F25496DB73E9 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> 3F2C5428-C65D-4F63-8BB3-AE3461403D1E 1 0.4716 0.67291 0.764 0.040 0.196 0.000
#> 505FACCE-D2A3-4AFF-8525-BC579E317D9C 3 0.4331 0.66813 0.000 0.288 0.712 0.000
#> 0C8730E9-90CC-4B76-9D20-60DA4881FA27 2 0.0188 0.87349 0.004 0.996 0.000 0.000
#> C6D0E763-7E74-45E5-8DA8-DDE62C43F784 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> 27CD53C1-E63D-4870-8B62-1235BF075A32 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> 51E96A1D-F65E-421F-BFAB-7716E16E530A 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 887E7408-C7D7-420F-A763-0EE70A316D17 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> 2AAAE1D7-309B-4F2D-A61C-C7C2FAB71AD7 3 0.4761 0.52685 0.000 0.372 0.628 0.000
#> ED57D62C-0904-4BDF-879B-C388CA1E301D 2 0.4454 0.48793 0.000 0.692 0.308 0.000
#> A2BB4331-B82A-4CFF-A490-5400A5085DFD 1 0.0469 0.88834 0.988 0.012 0.000 0.000
#> A17B743B-080B-4D00-9124-5CAECE38ABA5 1 0.0188 0.88976 0.996 0.004 0.000 0.000
#> 570F7FED-AD06-4274-97FA-BAFD9D5CB3F8 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> EE40EE80-4520-4643-B906-48246BA616A7 2 0.2412 0.83737 0.008 0.908 0.000 0.084
#> C075F09E-623C-46ED-B927-889B48F450B3 3 0.4998 0.04631 0.488 0.000 0.512 0.000
#> 0BDBBD67-9117-4C7C-8B3B-9463652DEA59 2 0.1389 0.86032 0.000 0.952 0.000 0.048
#> 580C059F-1B04-4229-8047-DCB3BC29FB01 2 0.3439 0.82038 0.048 0.868 0.000 0.084
#> 89BB88D0-CB32-406D-9B8D-642895E4FE9A 3 0.0376 0.82980 0.004 0.004 0.992 0.000
#> BBC99BA3-FD45-4D78-BFD9-0A452C99A364 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> 23890A5E-F5DD-4F67-9A92-524CFD760E24 1 0.4998 0.00370 0.512 0.488 0.000 0.000
#> 4872963F-DEE8-46A2-9173-90EF52BE061E 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> C3AEC49D-E7A2-4CFE-8F56-10578FE55294 2 0.0376 0.87231 0.000 0.992 0.004 0.004
#> 816CF68B-8476-4960-9F05-FB959A686323 3 0.4500 0.52751 0.316 0.000 0.684 0.000
#> EBA9865F-E212-4BCD-9816-7C001E7DFF99 4 0.2216 0.84326 0.000 0.092 0.000 0.908
#> 2B962C1A-B8DA-4A1E-ABD2-A4A9AC263740 3 0.5159 0.53583 0.000 0.364 0.624 0.012
#> B23A1419-0406-48BF-813B-B6ED6FD98789 2 0.3123 0.78558 0.156 0.844 0.000 0.000
#> 2F990386-E7DA-4D5A-BB71-4141905C4903 2 0.0937 0.86747 0.000 0.976 0.012 0.012
#> 15B12D3E-8CDE-4012-92DD-59423C4C6E8C 2 0.1557 0.84303 0.000 0.944 0.056 0.000
#> 7893DB86-CDA3-45DE-931F-CFBB52B64ACE 1 0.1557 0.86277 0.944 0.056 0.000 0.000
#> E0B47DDB-27D5-4631-9D96-E7C25F42CA48 2 0.4193 0.65120 0.268 0.732 0.000 0.000
#> 5E03E52F-957D-455B-A007-19714FAA818A 1 0.0921 0.88258 0.972 0.028 0.000 0.000
#> 6006A79E-F6AD-43F6-BAC9-159254B86F7A 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> 8A4B9352-D79A-46BB-8EE1-2BE5FBBB3EDF 1 0.0336 0.88753 0.992 0.000 0.008 0.000
#> AF331A84-397D-4E85-81FA-D4DD2D40E949 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> 1D87888D-7E1D-4327-8F57-BDBB95764E13 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> 35CD1BE6-D38C-4302-B0D6-188207F295B5 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> 89DACEFE-0514-4C0B-A40B-29FECBADA8C0 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> A0E8698C-155F-46AA-A1D9-B9DC653CE61E 2 0.4955 0.39225 0.000 0.648 0.008 0.344
#> 73CEF608-0FAD-4F1A-8A09-EA8883BEC344 1 0.0707 0.88591 0.980 0.020 0.000 0.000
#> C33059A9-A313-4806-B43B-0031365F3BE4 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> D9C02B51-F92B-4F5F-89AC-BD526832C915 1 0.0336 0.89014 0.992 0.008 0.000 0.000
#> 1122039D-5785-4F70-9916-17C585453512 3 0.2281 0.79255 0.096 0.000 0.904 0.000
#> F7849C4C-5733-40C6-A826-EF610E7CB14E 4 0.0000 0.91935 0.000 0.000 0.000 1.000
#> E678189F-D5CF-4C45-8E53-58ECB8448058 2 0.0657 0.87327 0.012 0.984 0.000 0.004
#> C56C7ED7-A684-40CC-B426-B108E2248467 3 0.0469 0.82879 0.012 0.000 0.988 0.000
#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.0524 0.87183 0.000 0.988 0.004 0.008
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 1 0.4992 0.06391 0.524 0.000 0.476 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 3 0.0469 0.82879 0.012 0.000 0.988 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 1 0.2542 0.83463 0.904 0.012 0.000 0.084
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 1 0.0592 0.88363 0.984 0.000 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.4996 0.03269 0.516 0.484 0.000 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.0188 0.87315 0.000 0.996 0.000 0.004
#> 1B73CE27-B464-41E6-BE27-90FA13683331 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.0672 0.87010 0.000 0.984 0.008 0.008
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.0592 0.88847 0.984 0.016 0.000 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 2 0.3024 0.79041 0.148 0.852 0.000 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 4 0.4661 0.46963 0.000 0.348 0.000 0.652
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 2 0.0817 0.87197 0.024 0.976 0.000 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.0376 0.87231 0.000 0.992 0.004 0.004
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 4 0.5696 0.06220 0.024 0.480 0.000 0.496
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 4 0.4238 0.74186 0.028 0.176 0.000 0.796
#> EB7883EB-0079-4548-9132-169E94A698BA 1 0.0188 0.89064 0.996 0.004 0.000 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.0817 0.88491 0.976 0.024 0.000 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 1 0.1297 0.87686 0.964 0.016 0.020 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.0592 0.88788 0.984 0.016 0.000 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.1940 0.80478 0.076 0.000 0.924 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0921 0.82571 0.028 0.000 0.972 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.4981 -0.06074 0.000 0.536 0.464 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 2 0.2844 0.84433 0.052 0.900 0.000 0.048
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 1 0.0000 0.88957 1.000 0.000 0.000 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 2 0.3074 0.78602 0.152 0.848 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 5 0.0000 0.9447 0.000 0.000 0.000 0.000 1.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 4 0.1502 0.8717 0.004 0.056 0.000 0.940 0.000
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0693 0.8337 0.012 0.000 0.980 0.008 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 4 0.3075 0.8034 0.000 0.048 0.092 0.860 0.000
#> BE685EF3-953B-483C-A99C-75FBF81D6615 1 0.4262 0.1351 0.560 0.440 0.000 0.000 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.2006 0.7491 0.916 0.000 0.072 0.012 0.000
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.0740 0.7677 0.980 0.008 0.004 0.008 0.000
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.2629 0.7157 0.860 0.000 0.004 0.136 0.000
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.0510 0.8247 0.000 0.016 0.984 0.000 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 5 0.0162 0.9434 0.000 0.000 0.004 0.000 0.996
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#> B6803321-BA08-464B-A8A1-A1A98A6C78DD 2 0.2179 0.7787 0.112 0.888 0.000 0.000 0.000
#> 1A8716BA-1C57-4354-BB23-67916F8983ED 3 0.1579 0.8341 0.032 0.000 0.944 0.024 0.000
#> AB4B5F5E-35AF-4609-A0D1-6E1771356D17 4 0.0404 0.9100 0.012 0.000 0.000 0.988 0.000
#> 45D6B2A4-98E3-4EAD-A86A-7F5FEF10C4F0 2 0.4562 -0.1141 0.000 0.496 0.496 0.008 0.000
#> 08C438CB-FDBA-4F47-A3E5-87B949C129B4 4 0.0290 0.9096 0.008 0.000 0.000 0.992 0.000
#> DB269B62-B5A6-405F-8D2E-0E2245D6EB5E 4 0.6161 0.4346 0.196 0.000 0.000 0.556 0.248
#> A655DC17-020D-4E51-A5C7-55D8C134FFC0 3 0.1981 0.8254 0.064 0.000 0.920 0.016 0.000
#> 79BA86D9-466F-48D7-B64B-F933B6995716 1 0.1764 0.7581 0.928 0.000 0.008 0.064 0.000
#> 9B65E4D0-7015-4192-9AF9-1383BD6B0E12 2 0.4306 0.1157 0.492 0.508 0.000 0.000 0.000
#> 1B73CE27-B464-41E6-BE27-90FA13683331 4 0.0290 0.9101 0.008 0.000 0.000 0.992 0.000
#> B4CD2742-8985-436A-B185-76D37DC4EFF3 2 0.3796 0.6046 0.300 0.700 0.000 0.000 0.000
#> F2A260A6-9EB6-4F54-83FD-F17F6F1F63E1 1 0.4237 0.6533 0.772 0.000 0.076 0.152 0.000
#> CC6EA54F-CD5F-4F4D-BE2A-A2739C2E3435 1 0.0451 0.7664 0.988 0.008 0.000 0.004 0.000
#> 55D67692-09C2-4EEB-8424-DE12B47FAF2C 5 0.2575 0.8455 0.100 0.012 0.000 0.004 0.884
#> E4FE16AB-D7FC-4183-B6A6-2A9CF8CA1D4F 1 0.3706 0.5682 0.756 0.004 0.236 0.004 0.000
#> 788B9881-8ED2-45AB-8F9E-227CB973F4DC 2 0.2806 0.7588 0.152 0.844 0.004 0.000 0.000
#> EB5C6373-9C28-4A80-B2BB-2883F5BF5348 1 0.4551 0.3997 0.636 0.008 0.000 0.008 0.348
#> F35D3CDD-78A2-4026-B275-8CCA93E32938 5 0.3611 0.7309 0.208 0.004 0.000 0.008 0.780
#> EB7883EB-0079-4548-9132-169E94A698BA 4 0.0162 0.9091 0.004 0.000 0.000 0.996 0.000
#> E6446572-BFA9-4018-89B3-7E4519EBE072 1 0.4443 0.0130 0.524 0.000 0.004 0.472 0.000
#> 18C27423-8BAB-4427-BCBB-F554C7A03C43 4 0.1892 0.8570 0.004 0.080 0.000 0.916 0.000
#> FC6B70B5-D69A-4039-9D3F-F7A25E980073 1 0.4313 0.3743 0.636 0.000 0.008 0.356 0.000
#> 1B81980F-2EA6-4B2D-99B3-860BBACC3E8E 3 0.1211 0.8243 0.000 0.024 0.960 0.016 0.000
#> 7018CAA2-8813-4AD8-9611-C8F0971C621F 3 0.0510 0.8247 0.000 0.016 0.984 0.000 0.000
#> A0C429D9-0638-4873-BFB4-00056AB4719F 2 0.2077 0.7881 0.084 0.908 0.008 0.000 0.000
#> 6F129BB5-D7FB-4799-82C1-5004C6337493 1 0.0486 0.7665 0.988 0.004 0.004 0.000 0.004
#> A66F8DE1-22CF-4A91-9064-F3C31CE38AFC 4 0.0880 0.9031 0.032 0.000 0.000 0.968 0.000
#> 682E834A-B44D-4B13-B26E-DAC1A9D8B83B 4 0.0566 0.9079 0.004 0.000 0.012 0.984 0.000
#> 2785594A-571A-46B4-A901-CB9C62DC6174 1 0.0854 0.7669 0.976 0.004 0.012 0.008 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> 922B74CF-AED1-4E9E-9650-4843F0A18820 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> CABE3151-1EB4-4A3B-82A4-0F698C51D824 6 0.2672 0.81403 0.000 0.080 0.000 0.000 0.052 0.868
#> F7946671-1EC2-4665-BB8D-CCBA87B69C33 3 0.0692 0.77631 0.020 0.000 0.976 0.000 0.004 0.000
#> BA66828A-AADE-4F85-B297-8BE56D8D6E38 6 0.3766 0.75606 0.000 0.068 0.100 0.000 0.024 0.808
#> BE685EF3-953B-483C-A99C-75FBF81D6615 5 0.5005 0.45605 0.164 0.192 0.000 0.000 0.644 0.000
#> 8A79D5E3-AE96-4353-A1F6-B9910988C412 1 0.3462 0.55331 0.816 0.000 0.100 0.000 0.080 0.004
#> 62DF1892-410B-420D-9EB2-ED032E55DEF7 1 0.2264 0.57289 0.888 0.096 0.000 0.000 0.012 0.004
#> 947659EE-D92A-4D41-AEBA-B1DB9000141D 1 0.4723 0.41460 0.664 0.000 0.000 0.000 0.232 0.104
#> 8414BA78-A8A9-4424-9C5A-9683128B1551 3 0.1333 0.76952 0.008 0.000 0.944 0.000 0.048 0.000
#> 01032C59-1724-4B6D-85E7-76C087E0F50F 4 0.0363 0.87686 0.000 0.000 0.000 0.988 0.012 0.000
#> A2A34964-65C3-4175-89B2-85405C5ABFE9 5 0.4805 0.47920 0.056 0.128 0.000 0.084 0.732 0.000
#> 33580931-57FC-41D9-91B5-21EAE9BC0AF7 1 0.4109 0.25069 0.576 0.012 0.000 0.000 0.412 0.000
#> 357A050A-ABEB-4516-933A-CDBEEEAD329F 5 0.4933 0.08229 0.068 0.396 0.000 0.000 0.536 0.000
#> 1C710173-532F-4435-BCE9-287AD8D247D9 5 0.3424 0.56702 0.204 0.024 0.000 0.000 0.772 0.000
#> 5AB5396F-925B-469C-B240-FB37991004DD 4 0.6524 0.32790 0.172 0.172 0.000 0.552 0.104 0.000
#> 3F172B98-8CF6-4644-B58A-9B50F76731D2 1 0.6354 0.38977 0.600 0.000 0.156 0.128 0.108 0.008
#> 08AA94B3-955B-45A2-A27C-524B5A6DDB79 6 0.0405 0.88125 0.000 0.008 0.000 0.000 0.004 0.988
#> F4D81754-F220-405F-9DDC-AA27EA1C529B 2 0.4098 0.23906 0.004 0.548 0.004 0.000 0.444 0.000
#> 6CCB94B6-2AF8-4CB7-8261-7A051ABA4783 2 0.4865 0.44715 0.004 0.652 0.000 0.096 0.248 0.000
#> E190109B-2CAE-4D04-82F3-F1EDDD137BB6 2 0.4034 0.48794 0.024 0.692 0.004 0.000 0.280 0.000
#> AB96957E-8B83-420D-876D-35DA9BC4A9B8 3 0.1970 0.73060 0.000 0.060 0.912 0.000 0.028 0.000
#> 04B7448C-5DA4-489D-89AC-2927C1EBECEA 2 0.3873 0.59368 0.124 0.772 0.000 0.000 0.104 0.000
#> 45A6FA0E-DA3E-4B29-9BB6-CED11625FDB6 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 5262FD57-1A06-4D0B-B9DD-85A601BA84BD 2 0.2203 0.60955 0.004 0.896 0.016 0.000 0.084 0.000
#> 840EA89B-ADA6-4697-B133-7DD1CE4275E0 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> AE03DEEA-AEE4-4D86-8D8E-13B6D81EA782 3 0.2998 0.70064 0.024 0.096 0.856 0.000 0.024 0.000
#> 0503F117-8779-46DD-AD24-E41DC25B0ADB 1 0.3201 0.47502 0.780 0.000 0.000 0.000 0.208 0.012
#> EE97212E-8D5D-4548-8DD2-317049601FDB 5 0.4453 0.35779 0.400 0.032 0.000 0.000 0.568 0.000
#> 8586E94A-F9B6-4387-A877-A4B118EC1784 5 0.3997 -0.03914 0.488 0.004 0.000 0.000 0.508 0.000
#> 73C3D0A1-3F9B-458F-9909-EF64332D32B5 1 0.4366 0.22041 0.540 0.000 0.000 0.440 0.016 0.004
#> 97C34F1F-2002-4771-8D99-511EA08591CD 6 0.4232 0.70448 0.152 0.000 0.040 0.000 0.044 0.764
#> 8F07ADA6-C2B7-474E-8AAC-FAC995B8C2A2 2 0.4293 0.31983 0.004 0.584 0.016 0.000 0.396 0.000
#> C880C6CA-292D-4CA3-840E-E905D4B5B277 6 0.3785 0.68042 0.000 0.196 0.012 0.000 0.028 0.764
#> C06D8112-0FA0-4607-988D-589D8694743F 6 0.5237 0.44806 0.172 0.000 0.000 0.000 0.220 0.608
#> CB56AEF9-15CC-414A-97E0-6AB5D480FC9B 5 0.5782 0.34617 0.252 0.000 0.108 0.036 0.600 0.004
#> 3679E6F5-5F44-424C-A3F7-D8AED7D8C5D5 1 0.6296 0.10819 0.392 0.304 0.000 0.000 0.296 0.008
#> EC7B4714-839A-4D6B-BA61-0A35B484DFC6 1 0.5206 0.31037 0.572 0.312 0.000 0.000 0.116 0.000
#> 72B5431D-32A6-4216-A49B-7E4F275D2FA3 6 0.1870 0.86211 0.012 0.004 0.012 0.000 0.044 0.928
#> A84EA172-9823-40E9-BC22-C882725DD1C8 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> 07609CEF-97F7-4BDF-9321-B907620E8A64 6 0.3394 0.77959 0.000 0.092 0.040 0.000 0.032 0.836
#> 5F28E34B-2267-4352-BBD2-17D86F2AE220 1 0.3999 -0.14509 0.500 0.000 0.000 0.000 0.496 0.004
#> 9DFED478-492A-401A-9742-14FA7D9AEFBC 1 0.2791 0.58306 0.852 0.016 0.008 0.000 0.000 0.124
#> 2FE8D6DA-BB60-4F02-AFF7-B9A9A5C139C4 2 0.1821 0.63685 0.040 0.928 0.008 0.000 0.024 0.000
#> 60EE5A75-84EC-419D-9540-0864A98EA293 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> C85272A2-1AA0-4FE1-B757-43EE7F179FC0 1 0.4546 0.52762 0.692 0.104 0.000 0.000 0.000 0.204
#> BFE95F66-6F9F-4431-B756-7A8DF5025DE0 3 0.5079 0.59580 0.224 0.000 0.628 0.000 0.148 0.000
#> C8C8CEF5-DD76-4680-89DE-D8C8E8261A70 3 0.2145 0.72326 0.000 0.072 0.900 0.000 0.028 0.000
#> 066B10C1-777F-4863-ACCA-6684310B913E 4 0.3099 0.78638 0.012 0.000 0.000 0.848 0.096 0.044
#> 4BC159E4-2342-4E62-9B8A-FDA31533EB3E 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 0752001B-A5C1-4E1A-A88D-2DCAE1667B53 2 0.3542 0.57444 0.052 0.788 0.000 0.000 0.160 0.000
#> 4A44F552-FC0B-45F9-95EA-C79B746B0D43 6 0.2745 0.80341 0.068 0.000 0.000 0.000 0.068 0.864
#> 4379559E-E467-49BD-9673-40A486146A3B 1 0.4505 0.41949 0.676 0.000 0.272 0.000 0.032 0.020
#> AFB4DDA2-FFB7-453F-A61D-334A62018A15 2 0.4367 0.33188 0.000 0.604 0.364 0.000 0.032 0.000
#> 07F15081-CEFC-47E3-BECC-8A8B52AB097E 1 0.3683 0.54459 0.784 0.000 0.160 0.000 0.052 0.004
#> C9993CB1-F653-4C1F-9D3B-52F638C24540 6 0.0363 0.88380 0.012 0.000 0.000 0.000 0.000 0.988
#> 311D089C-33F1-4722-9118-F56427C5C128 5 0.6468 0.08503 0.196 0.032 0.000 0.340 0.432 0.000
#> AFDBE143-6C36-4D68-A0D2-45CA3F0410B0 2 0.3290 0.56643 0.252 0.744 0.000 0.000 0.004 0.000
#> 7364131F-000B-45D7-9AA2-953BA00FEB4A 1 0.4939 0.03494 0.496 0.440 0.000 0.000 0.064 0.000
#> D97B363F-B7F4-46F3-B62F-E58549F401A8 5 0.3706 0.35613 0.380 0.000 0.000 0.000 0.620 0.000
#> 7243B18C-D841-4B86-A9F6-52EAF341E643 2 0.4885 0.47304 0.092 0.644 0.004 0.000 0.260 0.000
#> A77DDA16-167D-4444-8C58-526C99F2B406 1 0.3890 0.28900 0.596 0.004 0.000 0.000 0.400 0.000
#> F92010B1-94DC-4BD3-BDE9-B3FCBE957A62 2 0.4264 0.36263 0.376 0.604 0.012 0.000 0.008 0.000
#> 682099A3-074E-4CCD-A28B-748ADDA0DC01 1 0.6497 0.19852 0.412 0.068 0.000 0.000 0.116 0.404
#> 371149D5-6A07-4DE4-87A1-EDCA516D7A52 1 0.5127 0.15817 0.556 0.000 0.000 0.096 0.348 0.000
#> 7C72758D-B85C-405F-9A08-8EABCD455CDD 4 0.1556 0.84123 0.000 0.000 0.000 0.920 0.080 0.000
#> 2E8315CB-2AC5-4E31-A3D6-718859565AA7 4 0.1010 0.86427 0.004 0.000 0.000 0.960 0.036 0.000
#> CEE2741C-F60A-4E33-AB1F-3AC56245F780 4 0.0632 0.87136 0.000 0.000 0.000 0.976 0.024 0.000
#> 89C20FCC-0624-4EB8-AC83-37C033EC8DD7 4 0.5928 0.32251 0.120 0.032 0.000 0.536 0.312 0.000
#> 655C03A2-1D47-41DE-A5C9-91DF3F66F9AD 1 0.4035 0.46572 0.680 0.000 0.020 0.000 0.004 0.296
#> 530DDD97-7352-4F72-8891-D3B8DA235EFD 6 0.0146 0.88448 0.000 0.000 0.000 0.000 0.004 0.996
#> BD3C5FD0-9803-4C9F-8A7C-18B514E99C80 2 0.3773 0.53445 0.000 0.752 0.204 0.000 0.044 0.000
#> 5A0D2277-C465-4DA1-8D0B-19C36366B85C 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 2107C7A8-5A67-4667-9120-82C2F15630D6 1 0.3878 0.38585 0.668 0.320 0.008 0.000 0.004 0.000
#> DCD81371-253F-4672-AA92-9F27A338F68E 3 0.1564 0.74337 0.000 0.040 0.936 0.000 0.024 0.000
#> AB839BD2-BAC0-48CB-AF5C-C31ACDF6272F 1 0.4638 0.47739 0.672 0.000 0.232 0.000 0.096 0.000
#> C0711591-B971-4EC9-8205-0C1A5A6581B3 6 0.1951 0.83485 0.000 0.076 0.000 0.000 0.016 0.908
#> 3D4A257A-EF56-4269-8ED8-16B355DE7090 3 0.2000 0.77212 0.032 0.004 0.916 0.000 0.048 0.000
#> AFC2C1B1-D696-4797-AB1E-67F8D10A121B 5 0.5093 0.55945 0.152 0.040 0.000 0.112 0.696 0.000
#> 3C671A8D-0D10-4E66-A698-ADE98F4F8F1A 3 0.3185 0.75148 0.116 0.000 0.832 0.000 0.004 0.048
#> 6A611A0F-B310-4E69-B33B-84DFEFDFCF98 3 0.5456 0.51259 0.028 0.100 0.616 0.000 0.256 0.000
#> 8FEABF7B-E48D-48A9-8D60-90CCBB68A320 1 0.2194 0.59053 0.912 0.040 0.008 0.000 0.004 0.036
#> DD916B92-F40B-4D42-BE0E-A00C3AF6DB9A 3 0.4242 0.66564 0.136 0.032 0.768 0.000 0.064 0.000
#> A72CB3AB-D1CA-4D45-8F10-E2BF57FAD114 1 0.5036 0.44061 0.632 0.140 0.000 0.000 0.228 0.000
#> 5BFBB7A5-0B75-4DB0-9ED0-03B97A1CBD0D 3 0.3414 0.74006 0.020 0.052 0.852 0.024 0.052 0.000
#> 6FAEF85C-EA5E-4F5E-B8B3-E01455A9DD8A 6 0.1982 0.84687 0.016 0.004 0.000 0.000 0.068 0.912
#> 46351E5C-2438-4B6A-8343-DDF329086771 1 0.3534 0.48962 0.740 0.244 0.000 0.000 0.016 0.000
#> 193CCAB7-B6CA-4F5C-87CC-D5BA394209BA 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> 6F4C7C80-0C44-45BA-B540-39181A6A954B 3 0.0692 0.77657 0.020 0.000 0.976 0.000 0.004 0.000
#> 7DB4CA69-DE0A-4305-B645-4D25F9C7B3F3 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> B88C71E6-9239-4C74-B874-64BF27EDFA89 1 0.3720 0.48963 0.736 0.236 0.000 0.000 0.028 0.000
#> 9E10EE54-3F8A-40D5-943B-3BF3925AC8D2 6 0.1088 0.87490 0.024 0.000 0.000 0.000 0.016 0.960
#> 4D361EA8-1F79-4B89-841B-87F83215D805 1 0.5033 0.51300 0.688 0.000 0.200 0.000 0.060 0.052
#> 6A57D69C-8E19-47F2-8261-1419A45995A3 1 0.5959 0.24320 0.452 0.260 0.000 0.000 0.288 0.000
#> F10E1FF8-58F6-49FA-B4FD-47B31E8D0A1A 2 0.3969 0.41430 0.004 0.644 0.008 0.000 0.344 0.000
#> F2FFBB73-9948-4AA3-AED9-2DB59D55DDB2 1 0.5609 0.06552 0.464 0.000 0.008 0.000 0.416 0.112
#> 73F693A1-AC74-4648-8022-FC5340E5D1FE 4 0.0865 0.86405 0.000 0.000 0.000 0.964 0.036 0.000
#> 9BD4B68C-CECF-482E-B810-9C5FC0B12322 2 0.3840 0.59847 0.152 0.776 0.000 0.000 0.068 0.004
#> 31322670-76A2-4308-A71F-D8E00049519D 5 0.3925 0.40375 0.040 0.236 0.000 0.000 0.724 0.000
#> 4EA0F3B9-62B4-48F7-9CE1-6E04DA9D1C4D 6 0.0405 0.88125 0.000 0.008 0.000 0.000 0.004 0.988
#> 0F008777-8470-420B-9BFD-20F5DC5C86C4 2 0.2809 0.62884 0.128 0.848 0.020 0.000 0.004 0.000
#> 889327AA-5C8C-4CE8-8016-7B2978FCAE81 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> CB7C6043-CB13-4D0D-A997-2E74B58563AF 6 0.0000 0.88461 0.000 0.000 0.000 0.000 0.000 1.000
#> E8327684-CDED-42F2-875C-A99E4D9E5571 1 0.2972 0.56073 0.836 0.128 0.000 0.000 0.036 0.000
#> DCF88247-2CFB-4DEA-9668-4BDD9C71A8E1 3 0.2420 0.73632 0.040 0.076 0.884 0.000 0.000 0.000
#> C4E3A6C5-4267-4BBF-9D11-5FAB5C4BB18B 6 0.3072 0.80018 0.084 0.000 0.000 0.000 0.076 0.840
#> 6260F9B0-6665-4FFB-A0DA-7004AF3CEEB4 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> D09064DF-70AE-4A49-9F70-2A8093C96724 6 0.1141 0.86574 0.000 0.000 0.052 0.000 0.000 0.948
#> AE903797-7FFB-44A1-B834-C644784B5DC2 1 0.4091 0.54449 0.772 0.000 0.116 0.000 0.100 0.012
#> D18B79BE-2A49-4A4C-B5E3-AB8AE34E00E1 2 0.1498 0.63482 0.032 0.940 0.000 0.000 0.028 0.000
#> C44C898C-EEF9-4E03-911A-9D951312C380 4 0.0000 0.88101 0.000 0.000 0.000 1.000 0.000 0.000
#> 8967E2BE-2AAD-4B27-A29B-F9E48625A3F1 5 0.5639 0.43498 0.252 0.148 0.000 0.000 0.584 0.016
#> D04B63DE-03BA-4A63-92CA-D8054C3E238C 1 0.4219 0.22703 0.592 0.388 0.000 0.000 0.020 0.000
#> 06AEB932-C26F-40E0-BC3F-EEB16CBA854F 2 0.3858 0.56221 0.216 0.740 0.000 0.000 0.044 0.000
#> 291311CF-3283-4B1E-9CE5-F9D0D059B92E 1 0.5557 0.12350 0.512 0.004 0.000 0.128 0.356 0.000
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Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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