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 0.598 metric=euclidean
k=71
samples=20
Clustering
Self Organizing Maps 0.532 x=21
y=30
Clustering
Spectral Clustering 0.797 k=8 Clustering
clusterdp 0.62 k=14
dc=12.694891798584885
Clustering
HDBSCAN 0.704 minPts=5
k=7
Clustering
AGNES 0.704 method=weighted
metric=euclidean
k=7
Clustering
c-Means 0.605 k=6
m=1.01
Clustering
k-Medoids (PAM) 0.582 k=13 Clustering
DIANA 0.604 metric=euclidean
k=5
Clustering
DBSCAN 0.817 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.7 method=average
k=9
Clustering
fanny 0.597 k=16
membexp=2.0
Clustering
k-Means 0.569 k=7
nstart=10
Clustering
DensityCut 0.654 alpha=0.19523809523809524
K=6
Clustering
clusterONE 0.0 s=1
d=0.06666666666666667
Clustering
Affinity Propagation 0.53 dampfact=0.7725
preference=7.323976037645127
maxits=2000
convits=275
Clustering
Markov Clustering 0.47 I=9.091291291291292 Clustering
Transitivity Clustering 0.708 T=21.642019282410825 Clustering