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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=10.0
chang_pathbased
0.648
I=9.57237237237237
ppi_mips
0.993
I=4.1913913913913925
chang_spiral
0.0
I=5.403003003003003
astral_40_strsim
0.999
I=9.928728728728728
astral_40_seqsim_beh
0.999
I=10.0
fraenti_s3
0.0
I=7.7905905905905914
bone_marrow_fixLabels
0.0
I=1.126726726726727
fu_flame
0.0
I=4.342842842842843
coli_state
0.0
I=6.186986986986988
coli_find
0.0
I=1.1712712712712714
coli_need
0.0
I=5.598998998998999
coli_time
0.0
I=4.111211211211211
gionis_aggregation
0.0
I=3.968668668668669
veenman_r15
0.0
I=3.6924924924924927
zahn_compound
0.0
I=1.7236236236236238
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=2.480880880880881
astral1_161
0.964
I=10.0
tcga
0.0
I=7.460960960960961
bone_marrow
0.659
I=9.91981981981982
zachary
1.0
I=7.808408408408408