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=171
samples=20
Clustering
Self Organizing Maps 0.0 x=157
y=156
Clustering
Spectral Clustering 0.0 k=35 Clustering
clusterdp 0.0 k=22
dc=10.10258492774113
Clustering
HDBSCAN 0.0 minPts=5
k=34
Clustering
AGNES 0.0 method=single
metric=euclidean
k=46
Clustering
c-Means 0.0 k=243
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=58 Clustering
DIANA 0.0 metric=euclidean
k=170
Clustering
DBSCAN 0.0 eps=7.07180944941879
MinPts=301
Clustering
Hierarchical Clustering 0.0 method=complete
k=229
Clustering
fanny 0.0 k=46
membexp=2.0
Clustering
k-Means 0.0 k=61
nstart=10
Clustering
DensityCut 0.0 alpha=0.04517431972789116
K=8
Clustering
clusterONE 1.0 s=208
d=0.03333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=22.73081608741754
maxits=2000
convits=350
Clustering
Markov Clustering 1.0 I=3.63013013013013 Clustering
Transitivity Clustering 0.0 T=25.969407501941163 Clustering
MCODE 0.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=F
Clustering