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clustering evaluation framework
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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
0.965
k=8
m=1.01
chang_pathbased
0.798
k=2
m=1.5
ppi_mips
1.0
k=2
m=1.5
chang_spiral
0.496
k=2
m=1.5
astral_40_strsim
0.982
k=81
m=2.25
astral_40_seqsim_beh
1.0
k=33
m=5.0
fraenti_s3
0.918
k=2
m=2.25
bone_marrow_fixLabels
0.89
k=3
m=3.5
fu_flame
0.732
k=2
m=1.5
coli_state
0.643
k=2
m=2.25
coli_find
0.862
k=2
m=1.01
coli_need
0.854
k=2
m=2.25
coli_time
0.921
k=3
m=3.5
gionis_aggregation
0.993
k=3
m=1.01
veenman_r15
1.0
k=2
m=1.5
zahn_compound
1.0
k=2
m=3.5
synthetic_spirals
0.496
k=2
m=2.25
synthetic_cassini
0.947
k=7
m=1.5
twonorm_100d
0.99
k=20
m=2.25
twonorm_50d
0.99
k=13
m=5.0
synthetic_cuboid
1.0
k=4
m=3.5
astral1_161
0.992
k=28
m=1.5
tcga
0.988
k=3
m=2.25
bone_marrow
0.867
k=2
m=1.5
zachary
1.0
k=3
m=1.01