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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
1.0
I=1.3761761761761764
chang_pathbased
1.0
I=3.2114114114114116
ppi_mips
1.0
I=1.411811811811812
chang_spiral
1.0
I=5.456456456456457
astral_40_strsim
1.0
I=1.3227227227227227
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=5.144644644644645
bone_marrow_fixLabels
1.0
I=1.1979979979979982
fu_flame
1.0
I=9.296196196196195
coli_state
1.0
I=9.652552552552553
coli_find
1.0
I=9.322922922922924
coli_need
1.0
I=4.360660660660661
coli_time
1.0
I=2.07997997997998
gionis_aggregation
1.0
I=8.717117117117116
veenman_r15
1.0
I=1.5543543543543545
zahn_compound
1.0
I=7.166966966966968
synthetic_spirals
1.0
I=5.1001001001001
synthetic_cassini
1.0
I=8.663663663663664
twonorm_100d
1.0
I=7.567867867867869
twonorm_50d
1.0
I=9.492192192192192
synthetic_cuboid
1.0
I=5.892992992992993
astral1_161
1.0
I=1.117817817817818
tcga
1.0
I=7.095695695695696
bone_marrow
1.0
I=8.77947947947948
zachary
1.0
I=1.58998998998999