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 1.0 metric=euclidean
k=199
samples=20
Clustering
Self Organizing Maps 1.0 x=173
y=34
Clustering
Spectral Clustering 0.996 k=59 Clustering
clusterdp 0.978 k=5
dc=4.895619710727704
Clustering
HDBSCAN 1.0 minPts=27
k=200
Clustering
AGNES 1.0 method=ward
metric=euclidean
k=187
Clustering
c-Means 1.0 k=80
m=5.0
Clustering
k-Medoids (PAM) 1.0 k=188 Clustering
DIANA 1.0 metric=euclidean
k=183
Clustering
DBSCAN 1.0 eps=1.4686859132183112
MinPts=47
Clustering
Hierarchical Clustering 1.0 method=average
k=194
Clustering
fanny 1.0 k=68
membexp=4.363333333333333
Clustering
k-Means 1.0 k=194
nstart=10
Clustering
DensityCut 0.917 alpha=0.0
K=2
Clustering
clusterONE 0.994 s=5
d=0.7
Clustering
Markov Clustering 0.0 I=1.2336336336336338 Clustering
Transitivity Clustering 1.0 T=9.026758265425858 Clustering
MCODE 0.948 v=0.1
cutoff=4.895619710727704
haircut=F
fluff=T
Clustering