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 2.139 metric=euclidean
k=41
samples=20
Clustering
Self Organizing Maps 2.139 x=2
y=1
Clustering
Spectral Clustering 2.135 k=2 Clustering
clusterdp 2.316 k=2
dc=0.0
Clustering
HDBSCAN Infinity minPts=27
k=200
Clustering
AGNES Infinity method=average
metric=euclidean
k=200
Clustering
c-Means Infinity k=80
m=5.0
Clustering
k-Medoids (PAM) 2.139 k=4 Clustering
DIANA Infinity metric=euclidean
k=200
Clustering
DBSCAN Infinity eps=1.4686859132183112
MinPts=47
Clustering
Hierarchical Clustering Infinity method=complete
k=199
Clustering
fanny Infinity k=68
membexp=4.363333333333333
Clustering
k-Means 2.138 k=3
nstart=10
Clustering
DensityCut 2.005 alpha=0.0
K=2
Clustering
clusterONE 2.12 s=18
d=0.16666666666666666
Clustering
Markov Clustering -Infinity I=1.2336336336336338 Clustering
Transitivity Clustering Infinity T=9.026758265425858 Clustering
MCODE 2.066 v=0.0
cutoff=5.507572174568668
haircut=F
fluff=F
Clustering