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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
1.0
metric=euclidean
k=31
chang_pathbased
0.716
metric=euclidean
k=6
ppi_mips
0.569
metric=euclidean
k=975
chang_spiral
0.576
metric=euclidean
k=1
astral_40_strsim
0.408
metric=euclidean
k=470
astral_40_seqsim_beh
0.454
metric=euclidean
k=472
fraenti_s3
0.643
metric=euclidean
k=16
bone_marrow_fixLabels
0.852
metric=euclidean
k=20
fu_flame
0.759
metric=euclidean
k=2
coli_state
0.625
metric=euclidean
k=5
coli_find
0.356
metric=euclidean
k=3
coli_need
0.622
metric=euclidean
k=2
coli_time
0.513
metric=euclidean
k=1
gionis_aggregation
0.839
metric=euclidean
k=52
veenman_r15
0.96
metric=euclidean
k=17
zahn_compound
0.833
metric=euclidean
k=8
synthetic_spirals
0.706
metric=euclidean
k=1
synthetic_cassini
0.8
metric=euclidean
k=2
twonorm_100d
0.904
metric=euclidean
k=2
twonorm_50d
0.941
metric=euclidean
k=1
synthetic_cuboid
0.847
metric=euclidean
k=3
astral1_161
0.469
metric=euclidean
k=91
tcga
0.921
metric=euclidean
k=19
bone_marrow
0.82
metric=euclidean
k=1
zachary
0.775
metric=euclidean
k=16