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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
0.995
I=2.2225225225225227
chang_pathbased
0.696
I=9.305105105105104
ppi_mips
0.993
I=3.7370370370370374
chang_spiral
0.331
I=3.451951951951952
astral_40_strsim
0.991
I=8.832932932932934
astral_40_seqsim_beh
0.991
I=1.5632632632632633
fraenti_s3
0.067
I=6.6413413413413425
bone_marrow_fixLabels
0.361
I=1.1
fu_flame
0.536
I=7.095695695695696
coli_state
0.391
I=6.694794794794795
coli_find
0.127
I=2.1156156156156154
coli_need
0.387
I=8.628028028028028
coli_time
0.264
I=3.487587587587588
gionis_aggregation
0.217
I=2.418518518518519
veenman_r15
0.065
I=3.3005005005005006
zahn_compound
0.247
I=8.164764764764765
synthetic_spirals
0.498
I=8.432032032032032
synthetic_cassini
0.357
I=3.3450450450450453
twonorm_100d
0.497
I=5.536636636636637
twonorm_50d
0.497
I=4.1913913913913925
synthetic_cuboid
0.261
I=8.316216216216215
astral1_161
0.852
I=8.663663663663664
tcga
0.554
I=8.44094094094094
bone_marrow
0.777
I=10.0
zachary
1.0
I=1.500900900900901