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 0.517 metric=euclidean
k=71
samples=20
Clustering
Self Organizing Maps 0.469 x=2
y=1
Clustering
Spectral Clustering 0.693 k=8 Clustering
clusterdp 0.506 k=20
dc=23.436723320464406
Clustering
HDBSCAN 0.579 minPts=5
k=7
Clustering
AGNES 0.605 method=single
metric=euclidean
k=11
Clustering
c-Means 0.493 k=3
m=1.01
Clustering
k-Medoids (PAM) 0.489 k=3 Clustering
DIANA 0.545 metric=euclidean
k=5
Clustering
DBSCAN 0.812 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.605 method=average
k=9
Clustering
fanny 0.532 k=32
membexp=1.1
Clustering
k-Means 0.491 k=3
nstart=10
Clustering
DensityCut 0.553 alpha=0.06914682539682541
K=7
Clustering
clusterONE 0.333 s=260
d=0.16666666666666666
Clustering
Affinity Propagation 0.333 dampfact=0.9175
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 0.464 I=9.224924924924926 Clustering
Transitivity Clustering 0.626 T=21.642019282410825 Clustering