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
1.0
I=1.7147147147147148
chang_pathbased
1.0
I=1.9107107107107109
ppi_mips
1.0
I=1.8305305305305308
chang_spiral
1.0
I=8.013313313313315
astral_40_strsim
1.0
I=1.3405405405405406
astral_40_seqsim_beh
1.0
I=1.2247247247247248
fraenti_s3
1.0
I=3.229229229229229
bone_marrow_fixLabels
1.0
I=1.1
fu_flame
1.0
I=6.08008008008008
coli_state
1.0
I=7.407507507507508
coli_find
1.0
I=1.411811811811812
coli_need
1.0
I=6.436436436436437
coli_time
1.0
I=3.9152152152152153
gionis_aggregation
1.0
I=3.1757757757757763
veenman_r15
1.0
I=5.1980980980980975
zahn_compound
1.0
I=5.705905905905906
synthetic_spirals
1.0
I=6.445345345345345
synthetic_cassini
1.0
I=9.964364364364364
twonorm_100d
1.0
I=1.5632632632632633
twonorm_50d
1.0
I=5.501001001001001
synthetic_cuboid
1.0
I=7.247147147147147
astral1_161
1.0
I=1.6790790790790793
tcga
1.0
I=9.839639639639639
bone_marrow
1.0
I=8.004404404404404
zachary
1.0
I=1.1445445445445446