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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=1.7147147147147148
chang_pathbased
1.0
I=2.7303303303303306
ppi_mips
1.0
I=1.883983983983984
chang_spiral
1.0
I=9.608008008008008
astral_40_strsim
1.0
I=1.3405405405405406
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=6.774974974974976
bone_marrow_fixLabels
1.0
I=1.1
fu_flame
1.0
I=1.9552552552552553
coli_state
1.0
I=6.694794794794795
coli_find
1.0
I=4.2003003003003005
coli_need
1.0
I=1.108908908908909
coli_time
1.0
I=1.1
gionis_aggregation
1.0
I=1.1
veenman_r15
1.0
I=1.1801801801801801
zahn_compound
1.0
I=8.922022022022022
synthetic_spirals
1.0
I=3.2114114114114116
synthetic_cassini
1.0
I=9.26946946946947
twonorm_100d
1.0
I=5.492092092092093
twonorm_50d
1.0
I=6.302802802802803
synthetic_cuboid
1.0
I=5.331731731731732
astral1_161
1.0
I=1.7592592592592593
tcga
1.0
I=4.111211211211211
bone_marrow
1.0
I=4.084484484484484
zachary
1.0
I=1.9552552552552553