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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
0.995
metric=euclidean
k=25
chang_pathbased
0.745
metric=euclidean
k=76
ppi_mips
0.271
metric=euclidean
k=978
chang_spiral
0.714
metric=euclidean
k=1
astral_40_strsim
0.391
metric=euclidean
k=425
astral_40_seqsim_beh
0.434
metric=euclidean
k=457
fraenti_s3
0.769
metric=euclidean
k=16
bone_marrow_fixLabels
0.862
metric=euclidean
k=20
fu_flame
0.852
metric=euclidean
k=1
coli_state
0.698
metric=euclidean
k=1
coli_find
0.398
metric=euclidean
k=124
coli_need
0.739
metric=euclidean
k=1
coli_time
0.597
metric=euclidean
k=1
gionis_aggregation
0.879
metric=euclidean
k=10
veenman_r15
0.977
metric=euclidean
k=13
zahn_compound
0.8
metric=euclidean
k=10
synthetic_spirals
0.833
metric=euclidean
k=1
synthetic_cassini
0.844
metric=euclidean
k=2
twonorm_100d
0.95
metric=euclidean
k=1
twonorm_50d
0.97
metric=euclidean
k=5
synthetic_cuboid
0.911
metric=euclidean
k=3
astral1_161
0.53
metric=euclidean
k=13
tcga
0.94
metric=euclidean
k=75
bone_marrow
0.832
metric=euclidean
k=3
zachary
0.834
metric=euclidean
k=17