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 0.0 metric=euclidean
k=187
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=735
Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=7
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=79
k=761
Clustering
AGNES 0.0 method=single
metric=euclidean
k=317
Clustering
c-Means 0.0 k=502
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=637 Clustering
DIANA 0.0 metric=euclidean
k=770
Clustering
DBSCAN 0.0 eps=0.0
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=single
k=506
Clustering
fanny 0.0 k=96
membexp=2.0
Clustering
k-Means 0.0 k=352
nstart=10
Clustering
DensityCut 0.0 alpha=0.0015625
K=10
Clustering
clusterONE 1.0 s=656
d=0.9333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=38.815460837145814
maxits=4250
convits=500
Clustering
Markov Clustering 1.0 I=6.4008008008008 Clustering
Transitivity Clustering 0.0 T=38.58233494623203 Clustering
MCODE 0.0 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering