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clustering evaluation framework
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Markov 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
0.997
I=9.260560560560561
chang_pathbased
0.648
I=9.064564564564565
ppi_mips
0.993
I=5.251551551551553
chang_spiral
0.0
I=3.8083083083083085
astral_40_strsim
0.999
I=9.84854854854855
astral_40_seqsim_beh
0.999
I=9.93763763763764
fraenti_s3
0.0
I=4.458658658658659
bone_marrow_fixLabels
0.0
I=1.1979979979979982
fu_flame
0.0
I=9.706006006006005
coli_state
0.0
I=8.307307307307306
coli_find
0.0
I=5.964264264264266
coli_need
0.0
I=9.483283283283283
coli_time
0.0
I=4.592292292292293
gionis_aggregation
0.0
I=1.4652652652652653
veenman_r15
0.0
I=1.7503503503503506
zahn_compound
0.0
I=6.997697697697698
synthetic_spirals
0.5
I=8.797297297297296
synthetic_cassini
0.0
I=4.1913913913913925
twonorm_100d
0.0
I=5.037737737737738
twonorm_50d
0.0
I=8.36076076076076
synthetic_cuboid
0.0
I=3.3361361361361364
astral1_161
0.964
I=10.0
tcga
0.0
I=6.276076076076077
bone_marrow
0.659
I=9.982182182182182
zachary
1.0
I=2.97977977977978