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=31
samples=20
Clustering
Self Organizing Maps 0.451 x=2
y=2
Clustering
Spectral Clustering 0.032 k=11 Clustering
clusterdp 0.0 k=27
dc=0.0
Clustering
HDBSCAN 0.0 minPts=36
k=36
Clustering
AGNES 0.067 method=average
metric=euclidean
k=11
Clustering
c-Means 0.339 k=4
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=32 Clustering
DIANA 0.035 metric=euclidean
k=20
Clustering
DBSCAN 0.639 eps=0.020339198944763118
MinPts=2
Clustering
Hierarchical Clustering 0.0 method=single
k=5
Clustering
fanny 0.055 k=8
membexp=5.0
Clustering
k-Means 0.047 k=3
nstart=10
Clustering
DensityCut 0.199 alpha=0.4
K=2
Clustering
clusterONE 0.639 s=1
d=0.3
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 0.639 I=1.1979979979979982 Clustering
Transitivity Clustering 0.0 T=0.3566994649772271 Clustering
MCODE 0.639 v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering