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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
0.991
metric=euclidean
k=24
chang_pathbased
0.728
metric=euclidean
k=4
ppi_mips
0.334
metric=euclidean
k=978
chang_spiral
0.5
metric=euclidean
k=1
astral_40_strsim
0.495
metric=euclidean
k=425
astral_40_seqsim_beh
0.531
metric=euclidean
k=457
fraenti_s3
0.767
metric=euclidean
k=17
bone_marrow_fixLabels
0.896
metric=euclidean
k=20
fu_flame
0.857
metric=euclidean
k=2
coli_state
0.53
metric=euclidean
k=14
coli_find
0.244
metric=euclidean
k=21
coli_need
0.55
metric=euclidean
k=1
coli_time
0.404
metric=euclidean
k=5
gionis_aggregation
0.841
metric=euclidean
k=8
veenman_r15
0.979
metric=euclidean
k=13
zahn_compound
0.806
metric=euclidean
k=7
synthetic_spirals
0.667
metric=euclidean
k=1
synthetic_cassini
0.772
metric=euclidean
k=3
twonorm_100d
0.95
metric=euclidean
k=1
twonorm_50d
0.97
metric=euclidean
k=5
synthetic_cuboid
0.857
metric=euclidean
k=4
astral1_161
0.481
metric=euclidean
k=91
tcga
0.911
metric=euclidean
k=2
bone_marrow
0.858
metric=euclidean
k=1
zachary
0.718
metric=euclidean
k=9