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 0.814 metric=euclidean
k=71
samples=20
Clustering
Self Organizing Maps 0.748 x=21
y=30
Clustering
Spectral Clustering 0.898 k=8 Clustering
clusterdp 0.81 k=16
dc=13.671421936937572
Clustering
HDBSCAN 0.848 minPts=9
k=24
Clustering
AGNES 0.867 method=ward
metric=euclidean
k=10
Clustering
c-Means 0.823 k=6
m=1.01
Clustering
k-Medoids (PAM) 0.8 k=7 Clustering
DIANA 0.832 metric=euclidean
k=5
Clustering
DBSCAN 0.93 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.867 method=average
k=9
Clustering
fanny 0.829 k=44
membexp=1.1
Clustering
k-Means 0.798 k=7
nstart=10
Clustering
DensityCut 0.785 alpha=0.19523809523809524
K=6
Clustering
clusterONE 0.333 s=1
d=0.06666666666666667
Clustering
Affinity Propagation 0.735 dampfact=0.845
preference=0.0
maxits=2000
convits=425
Clustering
Markov Clustering 0.696 I=9.59019019019019 Clustering
Transitivity Clustering 0.871 T=21.642019282410825 Clustering