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=6
samples=20
Clustering
Self Organizing Maps 1.0 x=26
y=150
Clustering
Spectral Clustering 1.0 k=17 Clustering
clusterdp 1.0 k=18
dc=3.2635051036455756
Clustering
HDBSCAN 1.0 minPts=8
k=83
Clustering
AGNES 1.0 method=ward
metric=euclidean
k=61
Clustering
c-Means 1.0 k=64
m=5.0
Clustering
k-Medoids (PAM) 1.0 k=112 Clustering
DIANA 1.0 metric=euclidean
k=154
Clustering
DBSCAN 1.0 eps=3.0024246953539295
MinPts=208
Clustering
Hierarchical Clustering 1.0 method=single
k=184
Clustering
fanny 1.0 k=114
membexp=5.0
Clustering
k-Means 1.0 k=233
nstart=10
Clustering
DensityCut 1.0 alpha=0.921875
K=11
Clustering
clusterONE 0.0 s=200
d=1.0
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.9790515310936726
maxits=5000
convits=200
Clustering
Markov Clustering 0.0 I=3.3183183183183185 Clustering
Transitivity Clustering 1.0 T=3.649637539332169 Clustering
MCODE 0.999 v=0.8
cutoff=3.589855614010133
haircut=T
fluff=T
Clustering