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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=2.2136136136136138
chang_pathbased
0.47
I=9.5990990990991
ppi_mips
0.951
I=4.556656656656657
chang_spiral
0.0
I=4.111211211211211
astral_40_strsim
0.857
I=4.85955955955956
astral_40_seqsim_beh
0.832
I=1.5632632632632633
fraenti_s3
0.0
I=4.111211211211211
bone_marrow_fixLabels
0.0
I=1.1712712712712714
fu_flame
0.0
I=9.126926926926927
coli_state
0.0
I=2.56996996996997
coli_find
0.0
I=1.6879879879879882
coli_need
0.0
I=9.349649649649649
coli_time
0.0
I=6.837337337337337
gionis_aggregation
0.0
I=4.405205205205205
veenman_r15
0.0
I=9.59019019019019
zahn_compound
0.0
I=9.732732732732734
synthetic_spirals
0.0
I=8.95765765765766
synthetic_cassini
0.0
I=5.1001001001001
twonorm_100d
0.0
I=5.696996996996998
twonorm_50d
0.0
I=3.5054054054054054
synthetic_cuboid
0.0
I=1.1712712712712714
astral1_161
0.59
I=3.4341341341341343
tcga
0.0
I=8.191491491491492
bone_marrow
0.645
I=9.93763763763764
zachary
1.0
I=1.901801801801802