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=4
samples=20
Clustering
Self Organizing Maps 0.0 x=250
y=233
Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=22
dc=1.4104703215341545
Clustering
HDBSCAN 0.0 minPts=8
k=4
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=66
Clustering
c-Means 0.0 k=38
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=85 Clustering
DIANA 0.0 metric=euclidean
k=246
Clustering
DBSCAN 0.0 eps=0.20895856615320804
MinPts=34
Clustering
Hierarchical Clustering 0.0 method=complete
k=26
Clustering
fanny 0.0 k=57
membexp=2.0
Clustering
k-Means 0.0 k=11
nstart=10
Clustering
DensityCut 0.0 alpha=0.044568452380952375
K=13
Clustering
clusterONE 0.739 s=250
d=0.9666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering 0.739 I=6.382982982982983 Clustering
Transitivity Clustering 0.0 T=1.291087837418095 Clustering
MCODE 0.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=T
Clustering