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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=2.249249249249249
chang_pathbased
0.696
I=9.27837837837838
ppi_mips
0.993
I=4.93973973973974
chang_spiral
0.331
I=6.00880880880881
astral_40_strsim
0.991
I=8.797297297297296
astral_40_seqsim_beh
0.991
I=1.5632632632632633
fraenti_s3
0.067
I=8.04004004004004
bone_marrow_fixLabels
0.361
I=1.1979979979979982
fu_flame
0.536
I=6.6413413413413425
coli_state
0.391
I=1.9463463463463464
coli_find
0.127
I=9.545645645645646
coli_need
0.387
I=3.9864864864864864
coli_time
0.264
I=8.004404404404404
gionis_aggregation
0.217
I=1.9196196196196198
veenman_r15
0.065
I=5.109009009009009
zahn_compound
0.247
I=5.955355355355355
synthetic_spirals
0.498
I=9.955455455455455
synthetic_cassini
0.357
I=3.8172172172172174
twonorm_100d
0.497
I=6.3562562562562555
twonorm_50d
0.497
I=3.7370370370370374
synthetic_cuboid
0.261
I=1.2870870870870872
astral1_161
0.852
I=8.645845845845846
tcga
0.554
I=5.634634634634635
bone_marrow
0.777
I=9.955455455455455
zachary
1.0
I=1.5632632632632633