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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=9.51001001001001
ppi_mips
0.951
I=5.322822822822823
chang_spiral
0.0
I=6.721521521521523
astral_40_strsim
0.857
I=4.85955955955956
astral_40_seqsim_beh
0.832
I=1.5632632632632633
fraenti_s3
0.0
I=9.723823823823825
bone_marrow_fixLabels
0.0
I=1.1623623623623625
fu_flame
0.0
I=8.503303303303305
coli_state
0.0
I=4.244844844844845
coli_find
0.0
I=2.6768768768768765
coli_need
0.0
I=7.3006006006006015
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=4.057757757757758
twonorm_50d
0.0
I=7.38078078078078
synthetic_cuboid
0.0
I=2.1868868868868865
astral1_161
0.59
I=3.443043043043043
tcga
0.0
I=9.233833833833835
bone_marrow
0.645
I=9.955455455455455
zachary
1.0
I=1.9107107107107109