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How well do clustering methods perform on 'synthetic_cuboid'?


Program 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
CLARA 0.012 3.888 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 NaN 1.0 1.0
Self Organizing Maps 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
Spectral Clustering 0.542 3.003 0.709 0.803 0.046 0.004 0.664 0.441 0.843 0.843 1.0 0.39 0.996 0.727
clusterdp 0.409 3.892 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 0.539 1.0 1.0
HDBSCAN 0.0 NaN 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 NaN 1.0 1.0
AGNES 0.0 Infinity 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 NaN 1.0 1.0
c-Means 0.0 Infinity 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 0.563 1.0 1.0
k-Medoids (PAM) 0.012 4.082 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 0.562 1.0 1.0
DIANA 0.0 Infinity 0.857 0.911 0.0 0.0 NaN 0.729 0.909 0.909 1.0 NaN 1.0 0.857
DBSCAN 0.0 Infinity 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 NaN 1.0 1.0
Hierarchical Clustering 0.0 Infinity 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 NaN 1.0 1.0
fanny 0.0 Infinity 1.0 1.0 0.0 0.0 NaN 1.0 1.0 1.0 1.0 NaN 1.0 1.0
k-Means 0.014 4.082 1.0 1.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 0.563 1.0 1.0
DensityCut 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
clusterONE Infinity -Infinity 0.415 0.635 0.739 1.0 0.511 0.261 0.261 0.261 1.0 NaN 0.0 0.0
Affinity Propagation 0.0 Infinity 0.657 0.635 0.0 0.0 NaN 0.398 0.843 0.843 1.0 NaN 1.0 0.748
Markov Clustering Infinity -Infinity 0.415 0.635 0.739 1.0 0.511 0.261 0.261 0.261 1.0 NaN 0.0 0.0
Transitivity Clustering 0.0 NaN 0.961 0.943 0.0 0.0 NaN 0.887 0.971 NaN 1.0 NaN 1.0 0.945
MCODE 0.452 3.146 0.888 0.871 0.0 0.0 0.806 0.665 0.908 0.908 0.852 0.41 1.0 0.826