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 0.0 metric=euclidean
k=199
samples=20
Clustering
Self Organizing Maps 0.007 x=160
y=200
Clustering
Spectral Clustering 0.047 k=7 Clustering
clusterdp 0.095 k=17
dc=7.343429566091556
Clustering
HDBSCAN 0.25 minPts=7
k=193
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=187
Clustering
c-Means 0.0 k=190
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=188 Clustering
DIANA 0.0 metric=euclidean
k=183
Clustering
DBSCAN 0.0 eps=14.686859132183113
MinPts=7
Clustering
Hierarchical Clustering 0.0 method=average
k=194
Clustering
fanny 0.019 k=28
membexp=5.846666666666667
Clustering
k-Means 0.0 k=194
nstart=10
Clustering
DensityCut 0.188 alpha=0.0
K=2
Clustering
clusterONE 0.08 s=5
d=0.7
Clustering
Markov Clustering 0.503 I=1.2336336336336338 Clustering
Transitivity Clustering 0.0 T=7.835931849302902 Clustering
MCODE 0.269 v=0.3
cutoff=4.895619710727704
haircut=F
fluff=F
Clustering