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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=9.75055055055055
chang_pathbased
0.648
I=9.66146146146146
ppi_mips
0.993
I=3.9241241241241243
chang_spiral
0.0
I=7.1580580580580575
astral_40_strsim
0.999
I=9.946546546546546
astral_40_seqsim_beh
0.999
I=9.857457457457457
fraenti_s3
0.0
I=3.7815815815815816
bone_marrow_fixLabels
0.0
I=1.1979979979979982
fu_flame
0.0
I=2.365065065065065
coli_state
0.0
I=5.305005005005006
coli_find
0.0
I=3.38958958958959
coli_need
0.0
I=5.598998998998999
coli_time
0.0
I=4.342842842842843
gionis_aggregation
0.0
I=9.973273273273273
veenman_r15
0.0
I=9.643643643643644
zahn_compound
0.0
I=6.6502502502502505
synthetic_spirals
0.5
I=9.786186186186185
synthetic_cassini
0.0
I=3.0154154154154154
twonorm_100d
0.0
I=4.307207207207207
twonorm_50d
0.0
I=3.1935935935935937
synthetic_cuboid
0.0
I=4.333933933933935
astral1_161
0.964
I=10.0
tcga
0.0
I=7.345145145145146
bone_marrow
0.659
I=9.991091091091091
zachary
1.0
I=2.97977977977978