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=8
samples=20
Clustering
Self Organizing Maps 0.0 x=2
y=17
Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=8
dc=0.5746360569213221
Clustering
HDBSCAN 0.0 minPts=1
k=131
Clustering
AGNES 0.0 method=single
metric=euclidean
k=177
Clustering
c-Means 0.0 k=37
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=151 Clustering
DIANA 0.0 metric=euclidean
k=183
Clustering
DBSCAN 0.0 eps=1.3582306799958523
MinPts=200
Clustering
Hierarchical Clustering 0.0 method=single
k=211
Clustering
fanny 0.0 k=6
membexp=5.0
Clustering
k-Means 0.0 k=47
nstart=10
Clustering
DensityCut 0.0 alpha=0.25793650793650796
K=30
Clustering
clusterONE 0.739 s=25
d=0.5666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.3917973115372651
maxits=5000
convits=275
Clustering
Markov Clustering 0.739 I=1.9196196196196198 Clustering
Transitivity Clustering 0.0 T=1.408744687729586 Clustering
MCODE 0.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=T
Clustering