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=25
dc=0.1016959947238156
Clustering
HDBSCAN 1.0 minPts=10
k=2
Clustering
AGNES 1.0 method=weighted
metric=euclidean
k=1
Clustering
c-Means 0.867 k=2
m=5.0
Clustering
k-Medoids (PAM) 0.802 k=2 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=0.0
MinPts=15
Clustering
Hierarchical Clustering 0.973 method=complete
k=2
Clustering
fanny 1.0 k=5
membexp=2.0
Clustering
k-Means 0.901 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.8571428571428571
K=8
Clustering
clusterONE 1.0 s=34
d=0.3
Clustering
Affinity Propagation 1.0 dampfact=0.99
preference=0.0
maxits=2750
convits=500
Clustering
Markov Clustering 1.0 I=4.227027027027027 Clustering
Transitivity Clustering 1.0 T=0.04031192583646744 Clustering