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How well do clustering methods perform on 'twonorm_100d'?


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 0.39 2.016 0.667 0.833 0.0 0.0 0.705 0.497 0.538 0.538 1.0 NaN 1.0 0.232
Self Organizing Maps 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
Spectral Clustering 0.962 2.068 0.965 0.965 0.068 0.005 0.932 0.872 0.932 0.932 0.932 0.038 0.995 0.782
clusterdp 0.473 2.116 0.666 0.831 0.355 0.043 0.702 0.495 0.549 0.549 0.99 0.053 0.957 0.17
HDBSCAN 0.0 NaN 0.667 0.833 0.456 0.0 NaN 0.497 0.507 NaN 1.0 NaN 1.0 0.231
AGNES 0.0 Infinity 0.89 0.89 0.0 0.0 NaN 0.671 0.803 0.803 1.0 NaN 1.0 0.509
c-Means 0.0 Infinity 0.97 0.97 0.0 0.0 NaN 0.889 0.942 0.942 0.99 0.069 1.0 0.808
k-Medoids (PAM) 0.389 2.075 0.66 0.66 0.0 0.0 0.547 0.376 0.549 0.549 0.547 0.013 1.0 0.232
DIANA 0.0 Infinity 0.95 0.95 0.0 0.0 NaN 0.825 0.905 0.905 1.0 NaN 1.0 0.738
DBSCAN 0.0 Infinity 0.667 0.833 0.503 0.0 NaN 0.497 0.503 0.503 1.0 NaN 1.0 0.231
Hierarchical Clustering 0.0 Infinity 0.89 0.89 0.0 0.0 NaN 0.671 0.803 0.803 0.99 NaN 1.0 0.509
fanny 0.0 Infinity 0.899 0.898 0.05 0.0 NaN 0.697 0.819 0.819 1.0 0.071 1.0 0.606
k-Means 0.389 2.064 0.965 0.965 0.0 0.0 0.932 0.872 0.932 0.932 0.932 0.039 1.0 0.782
DensityCut 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
clusterONE 0.803 2.025 0.788 0.833 0.148 0.02 0.705 0.529 0.698 0.698 1.0 NaN 0.98 0.364
Affinity Propagation -- -- -- -- -- -- -- -- -- -- -- -- -- --
Markov Clustering Infinity -Infinity 0.667 0.833 0.503 1.0 0.705 0.497 0.497 0.497 1.0 NaN 0.0 0.0
Transitivity Clustering 0.0 Infinity 0.667 0.833 0.0 0.0 NaN 0.497 0.604 0.604 1.0 NaN 1.0 0.294
MCODE 0.919 1.854 0.667 0.833 0.389 0.063 0.705 0.497 0.551 0.551 1.0 NaN 0.937 0.152