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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=28.064244516622168
ppi_mips
1.0
T=1.0
chang_spiral
1.0
T=28.790850139418414
astral_40_strsim
1.0
T=24.12901515915916
astral_40_seqsim_beh
1.0
T=104.92819501894739
fraenti_s3
0.999
T=1080250.3385660197
bone_marrow_fixLabels
1.0
T=0.3854064424668327
fu_flame
1.0
T=12.926589714967228
coli_state
1.0
T=0.9992766611777584
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=37.80524864318606
veenman_r15
1.0
T=13.88743629468344
zahn_compound
1.0
T=36.59749304909367
synthetic_spirals
1.0
T=3.1263423423423427
synthetic_cassini
1.0
T=3.912285998124065
twonorm_100d
1.0
T=10.955197096581545
twonorm_50d
1.0
T=10.423406531249075
synthetic_cuboid
1.0
T=1.1906873251522891
astral1_161
1.0
T=93.42629003154325
tcga
1.0
T=0.8296115658595705
bone_marrow
1.0
T=0.6034573140368156
zachary
1.0
T=1.7377377377377377