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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
1.0
k=208
m=5.0
chang_pathbased
1.0
k=212
m=2.25
ppi_mips
1.0
k=399
m=1.01
chang_spiral
1.0
k=305
m=1.01
astral_40_strsim
1.0
k=1027
m=2.25
astral_40_seqsim_beh
1.0
k=310
m=2.25
fraenti_s3
1.0
k=1062
m=5.0
bone_marrow_fixLabels
0.742
k=3
m=3.5
fu_flame
1.0
k=42
m=1.01
coli_state
1.0
k=44
m=1.01
coli_find
1.0
k=67
m=2.25
coli_need
1.0
k=26
m=1.01
coli_time
1.0
k=16
m=1.5
gionis_aggregation
1.0
k=788
m=3.5
veenman_r15
1.0
k=352
m=2.25
zahn_compound
1.0
k=92
m=1.01
synthetic_spirals
1.0
k=234
m=1.5
synthetic_cassini
1.0
k=29
m=1.01
twonorm_100d
1.0
k=48
m=1.01
twonorm_50d
1.0
k=54
m=3.5
synthetic_cuboid
1.0
k=172
m=5.0
astral1_161
1.0
k=165
m=1.5
tcga
1.0
k=290
m=3.5
bone_marrow
1.0
k=33
m=1.01
zachary
1.0
k=11
m=3.5