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 1.0 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.961 x=2
y=1
Clustering
Spectral Clustering 0.942 k=2 Clustering
clusterdp 0.99 k=2
dc=0.0
Clustering
HDBSCAN 1.0 minPts=87
k=1
Clustering
AGNES 1.0 method=ward
metric=euclidean
k=1
Clustering
c-Means 0.99 k=13
m=5.0
Clustering
k-Medoids (PAM) 0.77 k=4 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=0.0
MinPts=27
Clustering
Hierarchical Clustering 0.99 method=single
k=2
Clustering
fanny 1.0 k=2
membexp=1.6933333333333331
Clustering
k-Means 0.951 k=3
nstart=10
Clustering
DensityCut 1.0 alpha=0.38095238095238093
K=10
Clustering
clusterONE 1.0 s=1
d=0.1
Clustering
Markov Clustering 1.0 I=1.1356356356356356 Clustering
Transitivity Clustering 1.0 T=0.2352249710860158 Clustering
MCODE 1.0 v=0.0
cutoff=4.283667246886741
haircut=T
fluff=F
Clustering