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 0.858 metric=euclidean
k=11
samples=20
Clustering
Self Organizing Maps 0.98 x=2
y=1
Clustering
Spectral Clustering 0.97 k=2 Clustering
clusterdp 0.831 k=2
dc=0.0
Clustering
HDBSCAN 0.833 minPts=87
k=1
Clustering
AGNES 0.914 method=flexible
metric=euclidean
k=2
Clustering
c-Means 0.975 k=2
m=1.01
Clustering
k-Medoids (PAM) 0.858 k=4 Clustering
DIANA 0.97 metric=euclidean
k=1
Clustering
DBSCAN 0.833 eps=0.9791239421455409
MinPts=73
Clustering
Hierarchical Clustering 0.88 method=average
k=12
Clustering
fanny 0.975 k=2
membexp=1.99
Clustering
k-Means 0.975 k=3
nstart=10
Clustering
DensityCut 0.833 alpha=0.38095238095238093
K=10
Clustering
clusterONE 0.924 s=2
d=0.06666666666666667
Clustering
Markov Clustering 0.833 I=1.1356356356356356 Clustering
Transitivity Clustering 0.833 T=0.2352249710860158 Clustering
MCODE 0.833 v=0.0
cutoff=4.283667246886741
haircut=F
fluff=F
Clustering