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
0.995
I=2.1512512512512516
chang_pathbased
0.696
I=9.438738738738738
ppi_mips
0.993
I=5.224824824824825
chang_spiral
0.331
I=7.38078078078078
astral_40_strsim
0.991
I=8.832932932932934
astral_40_seqsim_beh
0.991
I=1.5632632632632633
fraenti_s3
0.067
I=7.077877877877879
bone_marrow_fixLabels
0.361
I=1.2247247247247248
fu_flame
0.536
I=9.028928928928929
coli_state
0.391
I=6.6324324324324335
coli_find
0.127
I=2.667967967967968
coli_need
0.387
I=9.714914914914916
coli_time
0.264
I=6.837337337337337
gionis_aggregation
0.217
I=4.806106106106106
veenman_r15
0.065
I=9.59019019019019
zahn_compound
0.247
I=9.732732732732734
synthetic_spirals
0.498
I=8.904204204204206
synthetic_cassini
0.357
I=2.4452452452452453
twonorm_100d
0.497
I=3.4341341341341343
twonorm_50d
0.497
I=1.6968968968968972
synthetic_cuboid
0.261
I=6.374074074074075
astral1_161
0.852
I=8.663663663663664
tcga
0.554
I=4.574474474474474
bone_marrow
0.777
I=10.0
zachary
1.0
I=1.6256256256256256