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
0.997
I=9.394194194194194
chang_pathbased
0.648
I=9.795095095095094
ppi_mips
0.993
I=4.6991991991991995
chang_spiral
0.0
I=3.2470470470470474
astral_40_strsim
0.999
I=9.84854854854855
astral_40_seqsim_beh
0.999
I=9.93763763763764
fraenti_s3
0.0
I=5.6880880880880875
bone_marrow_fixLabels
0.0
I=1.1979979979979982
fu_flame
0.0
I=2.400700700700701
coli_state
0.0
I=5.002102102102103
coli_find
0.0
I=1.1712712712712714
coli_need
0.0
I=5.598998998998999
coli_time
0.0
I=4.351751751751752
gionis_aggregation
0.0
I=4.8684684684684685
veenman_r15
0.0
I=3.6924924924924927
zahn_compound
0.0
I=9.821821821821821
synthetic_spirals
0.5
I=8.432032032032032
synthetic_cassini
0.0
I=2.0532532532532537
twonorm_100d
0.0
I=4.307207207207207
twonorm_50d
0.0
I=3.647947947947948
synthetic_cuboid
0.0
I=1.6790790790790793
astral1_161
0.964
I=10.0
tcga
0.0
I=9.394194194194194
bone_marrow
0.659
I=9.91981981981982
zachary
1.0
I=8.36966966966967