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 0.645 metric=euclidean
k=4
samples=20
Clustering
Self Organizing Maps 0.639 x=2
y=2
Clustering
Spectral Clustering 0.432 k=26 Clustering
clusterdp 0.776 k=5
dc=0.020339198944763118
Clustering
HDBSCAN 0.583 minPts=9
k=23
Clustering
AGNES 0.684 method=average
metric=euclidean
k=4
Clustering
c-Means 0.735 k=3
m=5.0
Clustering
k-Medoids (PAM) 0.714 k=4 Clustering
DIANA 0.692 metric=euclidean
k=4
Clustering
DBSCAN 0.789 eps=0.5491583715086041
MinPts=5
Clustering
Hierarchical Clustering 0.789 method=average
k=4
Clustering
fanny 0.735 k=3
membexp=1.1
Clustering
k-Means 0.735 k=3
nstart=10
Clustering
DensityCut 0.66 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.612 s=2
d=0.7666666666666667
Clustering
Affinity Propagation 0.829 dampfact=0.7
preference=0.0
maxits=2750
convits=425
Clustering
Markov Clustering 0.645 I=9.93763763763764 Clustering
Transitivity Clustering 0.789 T=0.26324909144723435 Clustering