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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=9.706006006006005
chang_pathbased
0.648
I=9.804004004004005
ppi_mips
0.993
I=4.77937937937938
chang_spiral
0.0
I=4.601201201201201
astral_40_strsim
0.999
I=9.884184184184184
astral_40_seqsim_beh
0.999
I=10.0
fraenti_s3
0.0
I=6.98878878878879
bone_marrow_fixLabels
0.0
I=1.126726726726727
fu_flame
0.0
I=3.9152152152152153
coli_state
0.0
I=6.088988988988989
coli_find
0.0
I=3.7637637637637638
coli_need
0.0
I=3.933033033033033
coli_time
0.0
I=4.351751751751752
gionis_aggregation
0.0
I=5.144644644644645
veenman_r15
0.0
I=1.6523523523523527
zahn_compound
0.0
I=4.3784784784784785
synthetic_spirals
0.5
I=9.10910910910911
synthetic_cassini
0.0
I=6.115715715715716
twonorm_100d
0.0
I=4.325025025025026
twonorm_50d
0.0
I=3.8439439439439442
synthetic_cuboid
0.0
I=3.4341341341341343
astral1_161
0.964
I=10.0
tcga
0.0
I=9.536736736736737
bone_marrow
0.659
I=9.946546546546546
zachary
1.0
I=1.50980980980981