Clust
Eval
clustering evaluation framework
Welcome
Overview
Clustering Methods
Data Sets
Measures
Submit
Advanced
Help
About us
Location:
Clustering Methods
»
Markov Clustering
»
Best Parameters
Navigation:
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=9.349649649649649
ppi_mips
0.951
I=4.262662662662662
chang_spiral
0.0
I=5.794994994994996
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=1.2247247247247248
fu_flame
0.0
I=1.8483483483483483
coli_state
0.0
I=9.5990990990991
coli_find
0.0
I=1.6612612612612614
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=4.182482482482483
zahn_compound
0.0
I=5.812812812812813
synthetic_spirals
0.0
I=8.432032032032032
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=4.031031031031031
astral1_161
0.59
I=3.4252252252252253
tcga
0.0
I=1.1979979979979982
bone_marrow
0.645
I=9.955455455455455
zachary
1.0
I=1.8483483483483483