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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
0.955
I=2.1957957957957963
chang_pathbased
0.47
I=9.474374374374374
ppi_mips
0.951
I=3.6034034034034037
chang_spiral
0.0
I=3.184684684684685
astral_40_strsim
0.857
I=4.8684684684684685
astral_40_seqsim_beh
0.832
I=1.5632632632632633
fraenti_s3
0.0
I=3.0332332332332337
bone_marrow_fixLabels
0.0
I=1.1
fu_flame
0.0
I=6.543343343343344
coli_state
0.0
I=8.654754754754755
coli_find
0.0
I=7.345145145145146
coli_need
0.0
I=1.108908908908909
coli_time
0.0
I=7.808408408408408
gionis_aggregation
0.0
I=1.1
veenman_r15
0.0
I=7.077877877877879
zahn_compound
0.0
I=7.746046046046047
synthetic_spirals
0.0
I=9.394194194194194
synthetic_cassini
0.0
I=1.6523523523523527
twonorm_100d
0.0
I=2.16016016016016
twonorm_50d
0.0
I=2.3561561561561564
synthetic_cuboid
0.0
I=7.6213213213213225
astral1_161
0.59
I=3.443043043043043
tcga
0.0
I=4.03993993993994
bone_marrow
0.645
I=9.955455455455455
zachary
1.0
I=1.8483483483483483