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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=9.893093093093094
chang_pathbased
0.648
I=9.955455455455455
ppi_mips
0.993
I=4.36956956956957
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=9.287287287287286
bone_marrow_fixLabels
0.0
I=1.1979979979979982
fu_flame
0.0
I=2.400700700700701
coli_state
0.0
I=1.402902902902903
coli_find
0.0
I=5.705905905905906
coli_need
0.0
I=7.950950950950951
coli_time
0.0
I=9.91981981981982
gionis_aggregation
0.0
I=9.875275275275275
veenman_r15
0.0
I=4.405205205205205
zahn_compound
0.0
I=1.8572572572572574
synthetic_spirals
0.5
I=9.955455455455455
synthetic_cassini
0.0
I=4.004304304304305
twonorm_100d
0.0
I=6.543343343343344
twonorm_50d
0.0
I=1.3583583583583583
synthetic_cuboid
0.0
I=9.171471471471472
astral1_161
0.964
I=10.0
tcga
0.0
I=4.3784784784784785
bone_marrow
0.659
I=9.91091091091091
zachary
1.0
I=2.169069069069069