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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=9.554554554554555
chang_pathbased
0.648
I=9.153653653653654
ppi_mips
0.993
I=3.9152152152152153
chang_spiral
0.0
I=5.153553553553553
astral_40_strsim
0.999
I=9.893093093093094
astral_40_seqsim_beh
0.999
I=9.93763763763764
fraenti_s3
0.0
I=8.76166166166166
bone_marrow_fixLabels
0.0
I=1.126726726726727
fu_flame
0.0
I=1.1356356356356356
coli_state
0.0
I=1.7592592592592593
coli_find
0.0
I=2.2581581581581585
coli_need
0.0
I=5.598998998998999
coli_time
0.0
I=4.351751751751752
gionis_aggregation
0.0
I=5.955355355355355
veenman_r15
0.0
I=3.6835835835835837
zahn_compound
0.0
I=2.2136136136136138
synthetic_spirals
0.5
I=8.432032032032032
synthetic_cassini
0.0
I=2.0532532532532537
twonorm_100d
0.0
I=4.307207207207207
twonorm_50d
0.0
I=3.647947947947948
synthetic_cuboid
0.0
I=2.8461461461461464
astral1_161
0.964
I=10.0
tcga
0.0
I=6.445345345345345
bone_marrow
0.659
I=9.93763763763764
zachary
1.0
I=4.93083083083083