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 0.01 metric=euclidean
k=1
samples=20
Clustering
Self Organizing Maps 0.017 x=2
y=140
Clustering
Spectral Clustering 0.038 k=4 Clustering
clusterdp 0.053 k=2
dc=0.0
Clustering
HDBSCAN 0.078 minPts=24
k=2
Clustering
AGNES 0.071 method=flexible
metric=euclidean
k=1
Clustering
c-Means 0.069 k=20
m=2.25
Clustering
k-Medoids (PAM) 0.013 k=3 Clustering
DIANA 0.038 metric=euclidean
k=47
Clustering
DBSCAN NaN eps=17.60305130810116
MinPts=47
Clustering
Hierarchical Clustering 0.071 method=average
k=2
Clustering
fanny 0.071 k=28
membexp=7.626666666666667
Clustering
k-Means 0.039 k=79
nstart=10
Clustering
DensityCut 0.018 alpha=0.08333333333333331
K=4
Clustering
clusterONE 0.034 s=4
d=0.1
Clustering
Markov Clustering NaN I=3.4252252252252253 Clustering
Transitivity Clustering 0.078 T=2.6431007970121865 Clustering
MCODE 0.016 v=0.3
cutoff=3.035008846224338
haircut=F
fluff=F
Clustering