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Here you see a comparison matrix how well this clustering method performs on different datasets (rows). Where the performance is measured with different clustering quality measures (columns).

You can reorder the matrix by a certain column, to see on which dataset this clustering method performs best on, when measures by the corresponding clustering quality measure of that column.

How well does 'Self Organizing Maps' perform on different datasets?


Dataset Type Davies Bouldin Index (R) Dunn Index (R) F1-Score F2-Score False Discovery Rate False Positive Rate Fowlkes Mallows Index (R) Jaccard Index (R) Rand Index Rand Index (R) Sensitivity Silhouette Value (R) Specificity V-Measure
zachary -- -- -- -- -- -- -- -- -- -- -- -- -- --
bone_marrow 0.568 2.285 0.831 0.827 0.0 0.0 0.69 0.517 0.794 0.794 0.901 0.28 1.0 0.639
twonorm_50d 0.662 2.139 0.98 0.98 0.007 0.0 0.96 0.924 0.961 0.961 0.961 0.075 1.0 0.862
twonorm_100d 0.508 1.983 0.666 0.831 0.051 0.0 0.702 0.495 0.599 0.599 0.99 0.017 1.0 0.338
zahn_compound 0.337 5.204 0.611 0.764 0.0 0.0 0.676 0.457 0.805 0.805 1.0 0.638 1.0 0.643
veenman_r15 0.281 2.805 0.98 0.973 0.0 0.0 0.977 0.954 0.997 0.997 0.987 0.717 1.0 0.986
tcga -- -- -- -- -- -- -- -- -- -- -- -- -- --
astral1_161 -- -- -- -- -- -- -- -- -- -- -- -- -- --
synthetic_cuboid 0.437 3.079 0.651 0.779 0.0 0.0 0.661 0.436 0.853 0.853 0.931 0.509 1.0 0.769
synthetic_cassini 0.331 4.192 0.778 0.853 0.0 0.0 0.801 0.653 0.82 0.82 0.946 0.509 1.0 0.638
synthetic_spirals 0.342 3.129 0.504 0.504 0.0 0.0 0.496 0.33 0.515 0.515 0.496 0.372 1.0 0.271
gionis_aggregation 0.409 3.59 0.544 0.72 0.0 0.0 0.615 0.383 0.819 0.819 0.979 0.455 1.0 0.676
coli_time -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_need -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_find -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_state -- -- -- -- -- -- -- -- -- -- -- -- -- --
fraenti_s3 0.43 3.365 0.375 0.406 0.128 0.0 0.334 0.12 0.94 0.94 0.921 0.405 1.0 0.617
fu_flame 0.392 3.223 0.845 0.841 0.0 0.0 0.742 0.59 0.732 0.732 0.717 0.378 1.0 0.42
bone_marrow_fixLabels 0.665 2.285 0.754 0.874 0.451 0.465 0.741 0.549 0.703 NaN 1.0 0.209 0.535 0.665
astral_40_seqsim_beh -- -- -- -- -- -- -- -- -- -- -- -- -- --
astral_40_strsim -- -- -- -- -- -- -- -- -- -- -- -- -- --
chang_spiral 0.377 3.051 0.408 0.465 0.0 0.0 0.404 0.247 0.696 0.696 0.496 0.465 1.0 0.462
ppi_mips -- -- -- -- -- -- -- -- -- -- -- -- -- --
chang_pathbased 0.314 4.149 0.652 0.745 0.0 0.0 0.652 0.469 0.748 0.748 0.798 0.515 1.0 0.532
brown -- -- -- -- -- -- -- -- -- -- -- -- -- --