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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
1.0
I=1.4474474474474475
chang_pathbased
1.0
I=4.280480480480481
ppi_mips
1.0
I=2.088888888888889
chang_spiral
1.0
I=3.7014014014014016
astral_40_strsim
1.0
I=1.2692692692692693
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=8.066766766766767
bone_marrow_fixLabels
1.0
I=1.1979979979979982
fu_flame
1.0
I=3.6835835835835837
coli_state
1.0
I=2.659059059059059
coli_find
1.0
I=1.500900900900901
coli_need
1.0
I=2.3739739739739742
coli_time
1.0
I=9.91981981981982
gionis_aggregation
1.0
I=9.875275275275275
veenman_r15
1.0
I=6.953153153153154
zahn_compound
1.0
I=4.102302302302303
synthetic_spirals
1.0
I=6.757157157157157
synthetic_cassini
1.0
I=9.866366366366366
twonorm_100d
1.0
I=1.5632632632632633
twonorm_50d
1.0
I=8.628028028028028
synthetic_cuboid
1.0
I=5.429729729729731
astral1_161
1.0
I=1.7592592592592593
tcga
1.0
I=4.36956956956957
bone_marrow
1.0
I=6.703703703703703
zachary
1.0
I=1.5365365365365364