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clustering evaluation framework
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Transitivity Clustering
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Best Parameters
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General
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
T=323.3062153431158
chang_pathbased
1.0
T=27.47773992902296
ppi_mips
1.0
T=1.0
chang_spiral
1.0
T=28.517807303533516
astral_40_strsim
1.0
T=10.578300124124125
astral_40_seqsim_beh
1.0
T=92.18856869214362
fraenti_s3
0.999
T=1080250.3385660197
bone_marrow_fixLabels
1.0
T=0.5240550358740768
fu_flame
1.0
T=13.44365330356592
coli_state
1.0
T=0.999397217648132
coli_find
1.0
T=1.0000000000000002
coli_need
1.0
T=0.9998602584205872
coli_time
1.0
T=0.9997435964600633
gionis_aggregation
1.0
T=38.23264610986134
veenman_r15
1.0
T=13.943265184310308
zahn_compound
1.0
T=36.74476666297332
synthetic_spirals
1.0
T=3.1860180180180184
synthetic_cassini
1.0
T=3.622196655577792
twonorm_100d
1.0
T=7.6376498892972835
twonorm_50d
1.0
T=13.069687455966754
synthetic_cuboid
1.0
T=1.1044056349238622
astral1_161
1.0
T=326.9920151104013
tcga
1.0
T=0.592416155743217
bone_marrow
1.0
T=0.49351569811917717
zachary
1.0
T=1.4714714714714714