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clustering evaluation framework
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DIANA
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Best Parameters
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Best Qualities
Best Parameters
Hints:
Which parameter sets lead to the optimal clustering quality?
Please choose a clustering quality measure:
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
Dataset
Best quality
Parameter set
brown
0.996
metric=euclidean
k=25
chang_pathbased
0.604
metric=euclidean
k=5
ppi_mips
0.82
metric=euclidean
k=975
chang_spiral
0.476
metric=euclidean
k=37
astral_40_strsim
0.846
metric=euclidean
k=477
astral_40_seqsim_beh
0.846
metric=euclidean
k=487
fraenti_s3
0.748
metric=euclidean
k=16
bone_marrow_fixLabels
0.801
metric=euclidean
k=20
fu_flame
0.582
metric=euclidean
k=5
coli_state
0.372
metric=euclidean
k=147
coli_find
0.546
metric=euclidean
k=415
coli_need
0.359
metric=euclidean
k=101
coli_time
0.397
metric=euclidean
k=511
gionis_aggregation
0.807
metric=euclidean
k=18
veenman_r15
0.973
metric=euclidean
k=15
zahn_compound
0.799
metric=euclidean
k=6
synthetic_spirals
0.282
metric=euclidean
k=75
synthetic_cassini
0.635
metric=euclidean
k=3
twonorm_100d
0.738
metric=euclidean
k=1
twonorm_50d
0.835
metric=euclidean
k=4
synthetic_cuboid
0.857
metric=euclidean
k=4
astral1_161
0.613
metric=euclidean
k=91
tcga
0.799
metric=euclidean
k=75
bone_marrow
0.692
metric=euclidean
k=3
zachary
0.589
metric=euclidean
k=9