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=181
samples=20
Clustering
Self Organizing Maps 0.0 x=68
y=233
Clustering
Spectral Clustering 0.0 k=6 Clustering
clusterdp 0.0 k=5
dc=0.6624
Clustering
HDBSCAN 0.0 minPts=20
k=50
Clustering
AGNES 0.0 method=average
metric=euclidean
k=207
Clustering
c-Means 0.0 k=52
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=51 Clustering
DIANA 0.0 metric=euclidean
k=150
Clustering
DBSCAN 0.0 eps=1.4352000000000003
MinPts=225
Clustering
Hierarchical Clustering 0.0 method=single
k=177
Clustering
fanny 0.0 k=105
membexp=1.1
Clustering
k-Means 0.0 k=113
nstart=10
Clustering
DensityCut 0.0 alpha=0.03252551020408163
K=3
Clustering
clusterONE 0.502 s=150
d=0.16666666666666666
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=4.841741741741742 Clustering
Transitivity Clustering 0.0 T=3.0766126126126125 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering