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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
0.997
I=9.260560560560561
chang_pathbased
0.648
I=9.064564564564565
ppi_mips
0.993
I=4.004304304304305
chang_spiral
0.0
I=6.881881881881882
astral_40_strsim
0.999
I=9.91981981981982
astral_40_seqsim_beh
0.999
I=9.93763763763764
fraenti_s3
0.0
I=3.6835835835835837
bone_marrow_fixLabels
0.0
I=1.1979979979979982
fu_flame
0.0
I=2.578878878878879
coli_state
0.0
I=3.5321321321321326
coli_find
0.0
I=5.6524524524524535
coli_need
0.0
I=8.966566566566566
coli_time
0.0
I=9.03783783783784
gionis_aggregation
0.0
I=3.8439439439439442
veenman_r15
0.0
I=5.135735735735736
zahn_compound
0.0
I=6.115715715715716
synthetic_spirals
0.5
I=9.27837837837838
synthetic_cassini
0.0
I=2.32942942942943
twonorm_100d
0.0
I=5.037737737737738
twonorm_50d
0.0
I=8.36076076076076
synthetic_cuboid
0.0
I=3.3361361361361364
astral1_161
0.964
I=10.0
tcga
0.0
I=7.345145145145146
bone_marrow
0.659
I=9.991091091091091
zachary
1.0
I=6.24934934934935