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=1
samples=20
Clustering
Self Organizing Maps 0.961 x=2
y=1
Clustering
Spectral Clustering 0.942 k=2 Clustering
clusterdp 0.99 k=2
dc=0.0
Clustering
HDBSCAN 1.0 minPts=44
k=1
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=1
Clustering
c-Means 0.99 k=13
m=5.0
Clustering
k-Medoids (PAM) 0.77 k=4 Clustering
DIANA 1.0 metric=euclidean
k=19
Clustering
DBSCAN 1.0 eps=1.4686859132183112
MinPts=1
Clustering
Hierarchical Clustering 0.99 method=single
k=2
Clustering
fanny 1.0 k=2
membexp=6.1433333333333335
Clustering
k-Means 0.951 k=3
nstart=10
Clustering
DensityCut 1.0 alpha=0.8095238095238095
K=29
Clustering
clusterONE 1.0 s=3
d=0.8666666666666667
Clustering
Markov Clustering 1.0 I=1.2336336336336338 Clustering
Transitivity Clustering 1.0 T=0.6174655491007915 Clustering
MCODE 1.0 v=0.0
cutoff=4.283667246886741
haircut=T
fluff=T
Clustering