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=2.2225225225225227
chang_pathbased
0.696
I=9.697097097097096
ppi_mips
0.993
I=5.117917917917918
chang_spiral
0.331
I=3.398498498498499
astral_40_strsim
0.991
I=8.832932932932934
astral_40_seqsim_beh
0.991
I=1.5632632632632633
fraenti_s3
0.067
I=7.656956956956958
bone_marrow_fixLabels
0.361
I=1.1979979979979982
fu_flame
0.536
I=3.8528528528528527
coli_state
0.391
I=4.387387387387387
coli_find
0.127
I=7.345145145145146
coli_need
0.387
I=4.084484484484484
coli_time
0.264
I=2.249249249249249
gionis_aggregation
0.217
I=1.1
veenman_r15
0.065
I=2.1156156156156154
zahn_compound
0.247
I=7.656956956956958
synthetic_spirals
0.498
I=8.432032032032032
synthetic_cassini
0.357
I=3.3450450450450453
twonorm_100d
0.497
I=5.536636636636637
twonorm_50d
0.497
I=4.1913913913913925
synthetic_cuboid
0.261
I=5.3406406406406415
astral1_161
0.852
I=8.734934934934936
tcga
0.554
I=2.9174174174174174
bone_marrow
0.777
I=9.955455455455455
zachary
1.0
I=1.8483483483483483