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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=1.7147147147147148
chang_pathbased
1.0
I=6.6591591591591595
ppi_mips
1.0
I=1.794894894894895
chang_spiral
1.0
I=3.7726726726726727
astral_40_strsim
1.0
I=1.2514514514514514
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=5.313913913913915
bone_marrow_fixLabels
1.0
I=1.1979979979979982
fu_flame
1.0
I=6.382982982982983
coli_state
1.0
I=5.002102102102103
coli_find
1.0
I=6.766066066066067
coli_need
1.0
I=2.0443443443443443
coli_time
1.0
I=6.480980980980981
gionis_aggregation
1.0
I=6.748248248248248
veenman_r15
1.0
I=1.50980980980981
zahn_compound
1.0
I=4.592292292292293
synthetic_spirals
1.0
I=3.2203203203203206
synthetic_cassini
1.0
I=4.761561561561562
twonorm_100d
1.0
I=5.8306306306306315
twonorm_50d
1.0
I=5.296096096096097
synthetic_cuboid
1.0
I=2.1868868868868865
astral1_161
1.0
I=1.5187187187187188
tcga
1.0
I=7.291691691691692
bone_marrow
1.0
I=3.0421421421421426
zachary
1.0
I=1.1890890890890893