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 0.497 metric=euclidean
k=9
samples=20
Clustering
Self Organizing Maps 0.495 x=2
y=1
Clustering
Spectral Clustering 0.872 k=4 Clustering
clusterdp 0.495 k=2
dc=0.0
Clustering
HDBSCAN 0.497 minPts=140
k=7
Clustering
AGNES 0.671 method=complete
metric=euclidean
k=2
Clustering
c-Means 0.889 k=2
m=5.0
Clustering
k-Medoids (PAM) 0.376 k=3 Clustering
DIANA 0.825 metric=euclidean
k=47
Clustering
DBSCAN 0.497 eps=0.0
MinPts=20
Clustering
Hierarchical Clustering 0.671 method=single
k=2
Clustering
fanny 0.697 k=2
membexp=1.3966666666666667
Clustering
k-Means 0.872 k=2
nstart=10
Clustering
DensityCut 0.497 alpha=0.09523809523809523
K=10
Clustering
clusterONE 0.529 s=4
d=0.1
Clustering
Markov Clustering 0.497 I=1.117817817817818 Clustering
Transitivity Clustering 0.497 T=0.14582625086963785 Clustering
MCODE 0.497 v=0.3
cutoff=7.587522115560845
haircut=T
fluff=T
Clustering