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=1
samples=20
Clustering
Self Organizing Maps 0.901 x=2
y=1
Clustering
Spectral Clustering 0.901 k=26 Clustering
clusterdp 0.973 k=2
dc=0.1423743926133418
Clustering
HDBSCAN 1.0 minPts=10
k=1
Clustering
AGNES 1.0 method=average
metric=euclidean
k=1
Clustering
c-Means 0.867 k=3
m=5.0
Clustering
k-Medoids (PAM) 0.802 k=2 Clustering
DIANA 1.0 metric=euclidean
k=3
Clustering
DBSCAN 1.0 eps=0.020339198944763118
MinPts=21
Clustering
Hierarchical Clustering 0.973 method=complete
k=2
Clustering
fanny 1.0 k=6
membexp=2.0
Clustering
k-Means 0.901 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.5714285714285714
K=9
Clustering
clusterONE 1.0 s=2
d=0.1
Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 1.0 I=1.7503503503503506 Clustering
Transitivity Clustering 1.0 T=0.025042256959017652 Clustering