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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
0.995
I=2.1512512512512516
chang_pathbased
0.696
I=9.714914914914916
ppi_mips
0.993
I=4.173573573573573
chang_spiral
0.331
I=5.01991991991992
astral_40_strsim
0.991
I=8.824024024024025
astral_40_seqsim_beh
0.991
I=1.5721721721721722
fraenti_s3
0.067
I=6.578978978978979
bone_marrow_fixLabels
0.361
I=1.1445445445445446
fu_flame
0.536
I=6.276076076076077
coli_state
0.391
I=6.017717717717718
coli_find
0.127
I=7.817317317317317
coli_need
0.387
I=5.492092092092093
coli_time
0.264
I=8.093493493493494
gionis_aggregation
0.217
I=1.1
veenman_r15
0.065
I=9.349649649649649
zahn_compound
0.247
I=4.44974974974975
synthetic_spirals
0.498
I=9.955455455455455
synthetic_cassini
0.357
I=5.741541541541543
twonorm_100d
0.497
I=4.342842842842843
twonorm_50d
0.497
I=8.396396396396396
synthetic_cuboid
0.261
I=8.574574574574575
astral1_161
0.852
I=8.61911911911912
tcga
0.554
I=9.233833833833835
bone_marrow
0.777
I=9.946546546546546
zachary
1.0
I=1.50980980980981