Clusteval logo ClustEval clustering evaluation framework

Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:
Program Best quality Parameter set Clustering
CLARA 0.0 metric=euclidean
k=521
samples=20
Clustering
Self Organizing Maps 0.0 x=101
y=40
Clustering
Spectral Clustering 0.013 k=39 Clustering
clusterdp 0.003 k=17
dc=0.9295510122873538
Clustering
HDBSCAN 0.0 minPts=12
k=155
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=468
Clustering
c-Means 0.0 k=340
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=492 Clustering
DIANA 0.0 metric=euclidean
k=518
Clustering
DBSCAN 0.0 eps=0.9295510122873538
MinPts=120
Clustering
Hierarchical Clustering 0.0 method=complete
k=540
Clustering
fanny 0.0 k=295
membexp=5.0
Clustering
k-Means 0.0 k=514
nstart=10
Clustering
DensityCut 0.007 alpha=0.38095237722709063
K=28
Clustering
clusterONE 0.935 s=600
d=0.5333333333333333
Clustering
Affinity Propagation 0.004 dampfact=0.99
preference=10.457448888232731
maxits=4250
convits=275
Clustering
Markov Clustering 0.935 I=2.890690690690691 Clustering
Transitivity Clustering 0.0 T=13.873479072276723 Clustering
MCODE 0.017 v=0.5
cutoff=12.781326418951116
haircut=F
fluff=F
Clustering