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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
0.955
I=2.249249249249249
chang_pathbased
0.47
I=9.118018018018018
ppi_mips
0.951
I=4.031031031031031
chang_spiral
0.0
I=4.146846846846848
astral_40_strsim
0.857
I=4.85955955955956
astral_40_seqsim_beh
0.832
I=1.5632632632632633
fraenti_s3
0.0
I=7.247147147147147
bone_marrow_fixLabels
0.0
I=1.1
fu_flame
0.0
I=2.400700700700701
coli_state
0.0
I=8.218218218218219
coli_find
0.0
I=6.293893893893895
coli_need
0.0
I=3.558858858858859
coli_time
0.0
I=6.8284284284284285
gionis_aggregation
0.0
I=4.360660660660661
veenman_r15
0.0
I=5.403003003003003
zahn_compound
0.0
I=7.1491491491491495
synthetic_spirals
0.0
I=9.536736736736737
synthetic_cassini
0.0
I=1.6523523523523527
twonorm_100d
0.0
I=2.16016016016016
twonorm_50d
0.0
I=2.3561561561561564
synthetic_cuboid
0.0
I=9.296196196196195
astral1_161
0.59
I=3.4252252252252253
tcga
0.0
I=2.908508508508509
bone_marrow
0.645
I=9.955455455455455
zachary
1.0
I=1.8483483483483483