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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
0.955
I=2.1512512512512516
chang_pathbased
0.47
I=9.03783783783784
ppi_mips
0.951
I=5.456456456456457
chang_spiral
0.0
I=2.4452452452452453
astral_40_strsim
0.857
I=4.8684684684684685
astral_40_seqsim_beh
0.832
I=1.5632632632632633
fraenti_s3
0.0
I=4.601201201201201
bone_marrow_fixLabels
0.0
I=1.126726726726727
fu_flame
0.0
I=2.4274274274274275
coli_state
0.0
I=7.407507507507508
coli_find
0.0
I=9.073473473473474
coli_need
0.0
I=8.85965965965966
coli_time
0.0
I=6.391891891891892
gionis_aggregation
0.0
I=4.360660660660661
veenman_r15
0.0
I=9.002202202202202
zahn_compound
0.0
I=3.1045045045045048
synthetic_spirals
0.0
I=8.681481481481482
synthetic_cassini
0.0
I=7.371871871871872
twonorm_100d
0.0
I=8.05785785785786
twonorm_50d
0.0
I=3.95975975975976
synthetic_cuboid
0.0
I=8.574574574574575
astral1_161
0.59
I=3.4252252252252253
tcga
0.0
I=8.146946946946947
bone_marrow
0.645
I=9.946546546546546
zachary
1.0
I=1.50980980980981