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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=1.4741741741741743
chang_pathbased
1.0
I=7.594594594594595
ppi_mips
1.0
I=2.1868868868868865
chang_spiral
1.0
I=7.995495495495495
astral_40_strsim
1.0
I=1.2692692692692693
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=3.63013013013013
bone_marrow_fixLabels
1.0
I=1.1979979979979982
fu_flame
1.0
I=5.777177177177177
coli_state
1.0
I=3.6034034034034037
coli_find
1.0
I=3.6212212212212216
coli_need
1.0
I=2.3739739739739742
coli_time
1.0
I=1.1
gionis_aggregation
1.0
I=8.628028028028028
veenman_r15
1.0
I=1.1801801801801801
zahn_compound
1.0
I=9.492192192192192
synthetic_spirals
1.0
I=8.20930930930931
synthetic_cassini
1.0
I=2.8817817817817817
twonorm_100d
1.0
I=5.581181181181181
twonorm_50d
1.0
I=4.467567567567568
synthetic_cuboid
1.0
I=2.4452452452452453
astral1_161
1.0
I=1.1534534534534537
tcga
1.0
I=2.2848848848848853
bone_marrow
1.0
I=5.117917917917918
zachary
1.0
I=1.9552552552552553