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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=26.242450337826057
astral_40_strsim
1.0
T=21.025464296296295
astral_40_seqsim_beh
1.0
T=60.8027620142907
fraenti_s3
0.999
T=1080250.3385660197
bone_marrow_fixLabels
1.0
T=0.5045098597109411
fu_flame
1.0
T=13.44365330356592
coli_state
1.0
T=0.9992766611777584
coli_find
1.0
T=1.0000000000000002
coli_need
1.0
T=0.9997903876308808
coli_time
1.0
T=0.9997435964600633
gionis_aggregation
1.0
T=38.07722884925215
veenman_r15
1.0
T=13.88743629468344
zahn_compound
1.0
T=36.59749304909367
synthetic_spirals
1.0
T=3.0699819819819822
synthetic_cassini
1.0
T=3.622196655577792
twonorm_100d
1.0
T=8.512607394515111
twonorm_50d
1.0
T=12.86386560626649
synthetic_cuboid
1.0
T=1.0996993609114027
astral1_161
1.0
T=165.5876409141158
tcga
1.0
T=0.7860950952697485
bone_marrow
1.0
T=0.5643669617105441
zachary
1.0
T=0.6376376376376376