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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
0.923
I=2.1957957957957963
chang_pathbased
0.65
I=9.34074074074074
ppi_mips
0.821
I=4.565565565565565
chang_spiral
0.5
I=9.073473473473474
astral_40_strsim
0.645
I=4.61011011011011
astral_40_seqsim_beh
0.649
I=1.3138138138138138
fraenti_s3
0.125
I=8.574574574574575
bone_marrow_fixLabels
0.537
I=1.1
fu_flame
0.689
I=7.211511511511513
coli_state
0.53
I=5.376276276276276
coli_find
0.221
I=3.87957957957958
coli_need
0.55
I=8.752752752752754
coli_time
0.403
I=4.022122122122123
gionis_aggregation
0.345
I=1.1
veenman_r15
0.125
I=8.93983983983984
zahn_compound
0.381
I=9.064564564564565
synthetic_spirals
0.667
I=4.182482482482483
synthetic_cassini
0.524
I=5.126826826826828
twonorm_100d
0.667
I=3.1668668668668674
twonorm_50d
0.667
I=2.3472472472472474
synthetic_cuboid
0.415
I=7.095695695695696
astral1_161
0.596
I=3.558858858858859
tcga
0.678
I=1.2336336336336338
bone_marrow
0.783
I=9.955455455455455
zachary
1.0
I=1.8483483483483483