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 0.667 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.666 x=2
y=1
Clustering
Spectral Clustering 0.965 k=4 Clustering
clusterdp 0.666 k=2
dc=0.0
Clustering
HDBSCAN 0.667 minPts=140
k=7
Clustering
AGNES 0.89 method=flexible
metric=euclidean
k=1
Clustering
c-Means 0.97 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.66 k=3 Clustering
DIANA 0.95 metric=euclidean
k=47
Clustering
DBSCAN 0.667 eps=1.2140035384897352
MinPts=1
Clustering
Hierarchical Clustering 0.89 method=single
k=2
Clustering
fanny 0.899 k=2
membexp=1.3966666666666667
Clustering
k-Means 0.965 k=2
nstart=10
Clustering
DensityCut 0.667 alpha=0.09523809523809523
K=10
Clustering
clusterONE 0.788 s=4
d=0.1
Clustering
Markov Clustering 0.667 I=1.117817817817818 Clustering
Transitivity Clustering 0.667 T=0.8567292238591225 Clustering
MCODE 0.667 v=0.3
cutoff=7.587522115560845
haircut=T
fluff=T
Clustering