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
0.923
I=2.1957957957957963
chang_pathbased
0.65
I=9.42092092092092
ppi_mips
0.821
I=4.44084084084084
chang_spiral
0.5
I=5.438638638638639
astral_40_strsim
0.645
I=4.61011011011011
astral_40_seqsim_beh
0.649
I=1.3138138138138138
fraenti_s3
0.125
I=6.347347347347347
bone_marrow_fixLabels
0.537
I=1.1979979979979982
fu_flame
0.689
I=2.400700700700701
coli_state
0.53
I=3.3450450450450453
coli_find
0.221
I=1.1712712712712714
coli_need
0.55
I=2.5254254254254254
coli_time
0.403
I=1.1
gionis_aggregation
0.345
I=2.7125125125125127
veenman_r15
0.125
I=2.0354354354354354
zahn_compound
0.381
I=2.507607607607608
synthetic_spirals
0.667
I=2.400700700700701
synthetic_cassini
0.524
I=5.607907907907909
twonorm_100d
0.667
I=8.503303303303305
twonorm_50d
0.667
I=6.917517517517518
synthetic_cuboid
0.415
I=6.507707707707708
astral1_161
0.596
I=3.558858858858859
tcga
0.678
I=1.2336336336336338
bone_marrow
0.783
I=9.93763763763764
zachary
1.0
I=1.8483483483483483