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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
0.999
metric=euclidean
k=31
chang_pathbased
0.545
metric=euclidean
k=5
ppi_mips
0.33
metric=euclidean
k=978
chang_spiral
0.331
metric=euclidean
k=17
astral_40_strsim
0.179
metric=euclidean
k=425
astral_40_seqsim_beh
0.211
metric=euclidean
k=470
fraenti_s3
0.474
metric=euclidean
k=16
bone_marrow_fixLabels
0.732
metric=euclidean
k=20
fu_flame
0.61
metric=euclidean
k=1
coli_state
0.392
metric=euclidean
k=49
coli_find
0.128
metric=euclidean
k=13
coli_need
0.387
metric=euclidean
k=8
coli_time
0.264
metric=euclidean
k=1
gionis_aggregation
0.709
metric=euclidean
k=52
veenman_r15
0.923
metric=euclidean
k=13
zahn_compound
0.713
metric=euclidean
k=8
synthetic_spirals
0.498
metric=euclidean
k=1
synthetic_cassini
0.651
metric=euclidean
k=2
twonorm_100d
0.825
metric=euclidean
k=2
twonorm_50d
0.889
metric=euclidean
k=1
synthetic_cuboid
0.729
metric=euclidean
k=3
astral1_161
0.247
metric=euclidean
k=81
tcga
0.849
metric=euclidean
k=2
bone_marrow
0.689
metric=euclidean
k=3
zachary
0.601
metric=euclidean
k=9