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=245
samples=20
Clustering
Self Organizing Maps 0.0 x=26
y=191
Clustering
Spectral Clustering 0.0 k=4 Clustering
clusterdp 0.0 k=3
dc=3.0912
Clustering
HDBSCAN 0.0 minPts=15
k=13
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=58
Clustering
c-Means 0.0 k=194
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=222 Clustering
DIANA 0.0 metric=euclidean
k=215
Clustering
DBSCAN 0.0 eps=0.6624
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=complete
k=67
Clustering
fanny 0.0 k=95
membexp=2.0
Clustering
k-Means 0.0 k=191
nstart=10
Clustering
DensityCut 0.0 alpha=0.03512137276785712
K=4
Clustering
clusterONE 0.502 s=92
d=0.3333333333333333
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=5.803903903903905 Clustering
Transitivity Clustering 0.0 T=3.245693693693694 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering