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=188
samples=20
Clustering
Self Organizing Maps 0.0 x=173
y=34
Clustering
Spectral Clustering 0.004 k=59 Clustering
clusterdp 0.022 k=24
dc=4.406057739654934
Clustering
HDBSCAN 0.0 minPts=181
k=200
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=197
Clustering
c-Means 0.0 k=35
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=185 Clustering
DIANA 0.0 metric=euclidean
k=190
Clustering
DBSCAN 0.0 eps=5.874743652873245
MinPts=34
Clustering
Hierarchical Clustering 0.0 method=single
k=196
Clustering
fanny 0.0 k=74
membexp=5.846666666666667
Clustering
k-Means 0.0 k=192
nstart=10
Clustering
DensityCut 0.083 alpha=0.0
K=2
Clustering
clusterONE 0.006 s=1
d=0.6333333333333333
Clustering
Markov Clustering 1.0 I=8.975475475475475 Clustering
Transitivity Clustering 0.0 T=8.703323930182586 Clustering
MCODE 0.052 v=0.1
cutoff=4.895619710727704
haircut=T
fluff=F
Clustering