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 0.875 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.764 x=2
y=1
Clustering
Spectral Clustering 0.764 k=6 Clustering
clusterdp 0.908 k=6
dc=3.6781585066443236
Clustering
HDBSCAN 0.871 minPts=2
k=56
Clustering
AGNES 0.899 method=weighted
metric=euclidean
k=4
Clustering
c-Means 0.903 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.875 k=3 Clustering
DIANA 0.8 metric=euclidean
k=6
Clustering
DBSCAN 0.904 eps=29.42526805315459
MinPts=332
Clustering
Hierarchical Clustering 0.875 method=single
k=4
Clustering
fanny 0.875 k=3
membexp=1.1
Clustering
k-Means 0.875 k=5
nstart=10
Clustering
DensityCut 0.941 alpha=0.16338045634920634
K=7
Clustering
clusterONE 0.578 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.578 dampfact=0.7
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 0.578 I=3.1757757757757763 Clustering
Transitivity Clustering 0.883 T=28.386989075303035 Clustering
MCODE 0.829 v=0.8
cutoff=29.11875484426756
haircut=T
fluff=T
Clustering