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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
0.923
I=2.2136136136136138
chang_pathbased
0.65
I=9.314014014014015
ppi_mips
0.821
I=5.3584584584584585
chang_spiral
0.5
I=4.3784784784784785
astral_40_strsim
0.645
I=4.61011011011011
astral_40_seqsim_beh
0.649
I=1.3138138138138138
fraenti_s3
0.125
I=9.055655655655656
bone_marrow_fixLabels
0.537
I=1.1
fu_flame
0.689
I=7.6124124124124135
coli_state
0.53
I=1.1979979979979982
coli_find
0.221
I=5.9998998998999
coli_need
0.55
I=1.108908908908909
coli_time
0.403
I=1.1
gionis_aggregation
0.345
I=6.757157157157157
veenman_r15
0.125
I=9.091291291291292
zahn_compound
0.381
I=1.206906906906907
synthetic_spirals
0.667
I=2.6412412412412416
synthetic_cassini
0.524
I=6.721521521521523
twonorm_100d
0.667
I=3.6835835835835837
twonorm_50d
0.667
I=5.385185185185186
synthetic_cuboid
0.415
I=1.8038038038038038
astral1_161
0.596
I=3.5232232232232237
tcga
0.678
I=4.7081081081081075
bone_marrow
0.783
I=9.946546546546546
zachary
1.0
I=1.50980980980981