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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=9.75945945945946
chang_pathbased
0.648
I=10.0
ppi_mips
0.993
I=4.057757757757758
chang_spiral
0.0
I=4.316116116116116
astral_40_strsim
0.999
I=9.964364364364364
astral_40_seqsim_beh
0.999
I=9.866366366366366
fraenti_s3
0.0
I=8.36076076076076
bone_marrow_fixLabels
0.0
I=1.126726726726727
fu_flame
0.0
I=4.921921921921922
coli_state
0.0
I=1.3672672672672674
coli_find
0.0
I=2.961961961961962
coli_need
0.0
I=6.89079079079079
coli_time
0.0
I=4.111211211211211
gionis_aggregation
0.0
I=5.1001001001001
veenman_r15
0.0
I=4.512112112112113
zahn_compound
0.0
I=2.739239239239239
synthetic_spirals
0.5
I=9.59019019019019
synthetic_cassini
0.0
I=7.104604604604605
twonorm_100d
0.0
I=4.031031031031031
twonorm_50d
0.0
I=9.786186186186185
synthetic_cuboid
0.0
I=6.1602602602602605
astral1_161
0.964
I=9.973273273273273
tcga
0.0
I=8.770570570570571
bone_marrow
0.659
I=9.946546546546546
zachary
1.0
I=1.50980980980981