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=137
samples=20
Clustering
Self Organizing Maps 0.0 x=73
y=208
Clustering
Spectral Clustering 0.002 k=34 Clustering
clusterdp 0.0 k=24
dc=3.9355925715054516
Clustering
HDBSCAN 0.0 minPts=92
k=228
Clustering
AGNES 0.0 method=single
metric=euclidean
k=62
Clustering
c-Means 0.0 k=215
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=166 Clustering
DIANA 0.0 metric=euclidean
k=113
Clustering
DBSCAN 0.0 eps=3.44364350006727
MinPts=32
Clustering
Hierarchical Clustering 0.0 method=complete
k=32
Clustering
fanny 0.0 k=118
membexp=5.0
Clustering
k-Means 0.0 k=106
nstart=10
Clustering
DensityCut 0.0 alpha=0.6714285714285714
K=9
Clustering
clusterONE 1.0 s=144
d=0.26666666666666666
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=14.758472143145443
maxits=3500
convits=425
Clustering
Markov Clustering 1.0 I=9.073473473473474 Clustering
Transitivity Clustering 0.0 T=14.330048026877959 Clustering
MCODE 0.009 v=0.3
cutoff=13.52859946454999
haircut=T
fluff=T
Clustering