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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 'DensityCut' 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 0.623 2.519 0.894 0.894 0.23 0.15 0.804 0.672 0.846 0.846 1.0 NaN 0.85 0.66
twonorm_50d 0.968 2.005 0.737 0.833 0.188 0.083 0.705 0.497 0.651 0.651 1.0 NaN 0.917 0.318
twonorm_100d 0.96 2.035 0.667 0.833 0.501 0.733 0.705 0.497 0.501 0.501 1.0 NaN 0.267 0.081
zahn_compound 0.337 5.204 0.888 0.941 0.192 0.065 0.898 0.807 0.941 0.941 1.0 NaN 0.935 0.912
veenman_r15 0.221 5.725 0.997 0.997 0.007 0.0 0.993 0.987 0.999 0.999 1.0 NaN 1.0 0.994
tcga -- -- -- -- -- -- -- -- -- -- -- -- -- --
astral1_161 -- -- -- -- -- -- -- -- -- -- -- -- -- --
synthetic_cuboid 0.418 3.892 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
synthetic_cassini 0.439 4.24 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
synthetic_spirals 0.694 2.881 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
gionis_aggregation 0.334 3.729 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
coli_time -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_need -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_find -- -- -- -- -- -- -- -- -- -- -- -- -- --
coli_state -- -- -- -- -- -- -- -- -- -- -- -- -- --
fraenti_s3 0.433 3.26 0.861 0.861 0.248 0.018 0.754 0.606 0.967 0.967 1.0 NaN 0.982 0.803
fu_flame 0.562 2.638 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
bone_marrow_fixLabels 0.623 NaN 0.918 0.918 0.199 0.127 0.852 0.74 0.885 NaN 1.0 0.292 0.873 0.8
astral_40_seqsim_beh -- -- -- -- -- -- -- -- -- -- -- -- -- --
astral_40_strsim -- -- -- -- -- -- -- -- -- -- -- -- -- --
chang_spiral 0.734 2.55 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
ppi_mips -- -- -- -- -- -- -- -- -- -- -- -- -- --
chang_pathbased 0.478 4.149 0.76 0.87 0.005 0.0 0.738 0.553 0.785 0.785 1.0 NaN 1.0 0.654
brown -- -- -- -- -- -- -- -- -- -- -- -- -- --