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 0.769 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.611 x=2
y=1
Clustering
Spectral Clustering 0.8 k=20 Clustering
clusterdp 0.868 k=17
dc=15.938686862125401
Clustering
HDBSCAN 0.878 minPts=2
k=56
Clustering
AGNES 0.878 method=complete
metric=euclidean
k=56
Clustering
c-Means 0.833 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.769 k=3 Clustering
DIANA 0.806 metric=euclidean
k=6
Clustering
DBSCAN 0.886 eps=29.42526805315459
MinPts=332
Clustering
Hierarchical Clustering 0.874 method=single
k=57
Clustering
fanny 0.811 k=16
membexp=5.0
Clustering
k-Means 0.769 k=5
nstart=10
Clustering
DensityCut 0.888 alpha=0.16338045634920634
K=7
Clustering
clusterONE 0.381 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.581 dampfact=0.99
preference=9.195396266610809
maxits=3500
convits=425
Clustering
Markov Clustering 0.381 I=3.1757757757757763 Clustering
Transitivity Clustering 0.848 T=30.08063563491904 Clustering
MCODE 0.825 v=0.8
cutoff=29.11875484426756
haircut=T
fluff=T
Clustering