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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=1.4207207207207209
chang_pathbased
1.0
I=8.27167167167167
ppi_mips
1.0
I=1.8750750750750753
chang_spiral
1.0
I=5.429729729729731
astral_40_strsim
1.0
I=1.1979979979979982
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=3.5321321321321326
bone_marrow_fixLabels
1.0
I=1.1712712712712714
fu_flame
1.0
I=2.6768768768768765
coli_state
1.0
I=7.336236236236235
coli_find
1.0
I=9.91091091091091
coli_need
1.0
I=7.55005005005005
coli_time
1.0
I=1.1623623623623625
gionis_aggregation
1.0
I=5.919719719719721
veenman_r15
1.0
I=8.743843843843845
zahn_compound
1.0
I=6.480980980980981
synthetic_spirals
1.0
I=8.253853853853855
synthetic_cassini
1.0
I=1.5276276276276277
twonorm_100d
1.0
I=8.12912912912913
twonorm_50d
1.0
I=4.725925925925926
synthetic_cuboid
1.0
I=6.133533533533533
astral1_161
1.0
I=1.3672672672672674
tcga
1.0
I=2.65015015015015
bone_marrow
1.0
I=4.03993993993994
zachary
1.0
I=1.9552552552552553