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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=9.67927927927928
chang_pathbased
0.648
I=9.305105105105104
ppi_mips
0.993
I=5.242642642642642
chang_spiral
0.0
I=2.4096096096096096
astral_40_strsim
0.999
I=9.893093093093094
astral_40_seqsim_beh
0.999
I=9.93763763763764
fraenti_s3
0.0
I=7.345145145145146
bone_marrow_fixLabels
0.0
I=1.117817817817818
fu_flame
0.0
I=2.1156156156156154
coli_state
0.0
I=1.2959959959959961
coli_find
0.0
I=8.013313313313315
coli_need
0.0
I=5.598998998998999
coli_time
0.0
I=9.91981981981982
gionis_aggregation
0.0
I=9.875275275275275
veenman_r15
0.0
I=4.405205205205205
zahn_compound
0.0
I=1.8572572572572574
synthetic_spirals
0.5
I=9.955455455455455
synthetic_cassini
0.0
I=4.004304304304305
twonorm_100d
0.0
I=3.229229229229229
twonorm_50d
0.0
I=8.512212212212212
synthetic_cuboid
0.0
I=6.4008008008008
astral1_161
0.964
I=9.93763763763764
tcga
0.0
I=6.445345345345345
bone_marrow
0.659
I=9.973273273273273
zachary
1.0
I=9.002202202202202