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 0.689 metric=euclidean
k=71
samples=20
Clustering
Self Organizing Maps 0.652 x=2
y=1
Clustering
Spectral Clustering 0.832 k=8 Clustering
clusterdp 0.68 k=20
dc=23.436723320464406
Clustering
HDBSCAN 0.736 minPts=9
k=24
Clustering
AGNES 0.775 method=single
metric=euclidean
k=11
Clustering
c-Means 0.686 k=6
m=1.01
Clustering
k-Medoids (PAM) 0.66 k=3 Clustering
DIANA 0.716 metric=euclidean
k=5
Clustering
DBSCAN 0.896 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.775 method=average
k=9
Clustering
fanny 0.706 k=44
membexp=1.1
Clustering
k-Means 0.662 k=3
nstart=10
Clustering
DensityCut 0.738 alpha=0.06914682539682541
K=7
Clustering
clusterONE 0.577 s=1
d=0.06666666666666667
Clustering
Affinity Propagation 0.577 dampfact=0.9175
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 0.647 I=9.091291291291292 Clustering
Transitivity Clustering 0.783 T=21.642019282410825 Clustering