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 1.0 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.496 x=2
y=1
Clustering
Spectral Clustering 0.854 k=3 Clustering
clusterdp 1.0 k=3
dc=22.225686841030484
Clustering
HDBSCAN 1.0 minPts=60
k=1
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=1
Clustering
c-Means 0.496 k=2
m=1.01
Clustering
k-Medoids (PAM) 0.5 k=13 Clustering
DIANA 1.0 metric=euclidean
k=2
Clustering
DBSCAN 1.0 eps=4.041033971096452
MinPts=239
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 1.0 k=8
membexp=5.0
Clustering
k-Means 0.496 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.03968253968253968
K=7
Clustering
clusterONE 1.0 s=166
d=0.3
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.0
maxits=3500
convits=275
Clustering
Markov Clustering 1.0 I=4.423023023023023 Clustering
Transitivity Clustering 1.0 T=12.650984729333487 Clustering
MCODE 0.496 v=0.7
cutoff=17.679523623546974
haircut=F
fluff=F
Clustering