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 0.0 metric=euclidean
k=28
samples=20
Clustering
Self Organizing Maps 0.0 x=34
y=10
Clustering
Spectral Clustering 0.423 k=33 Clustering
clusterdp 0.0 k=25
dc=0.2440703873371574
Clustering
HDBSCAN 0.0 minPts=23
k=34
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=23
Clustering
c-Means 0.0 k=11
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=28 Clustering
DIANA 0.0 metric=euclidean
k=25
Clustering
DBSCAN 0.0 eps=0.020339198944763118
MinPts=2
Clustering
Hierarchical Clustering 0.0 method=complete
k=33
Clustering
fanny 0.007 k=18
membexp=1.1
Clustering
k-Means 0.0 k=26
nstart=10
Clustering
DensityCut 0.15 alpha=0.6190476190476191
K=2
Clustering
clusterONE 0.057 s=4
d=0.8666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.6101759683428936
maxits=4250
convits=275
Clustering
Markov Clustering 0.341 I=9.946546546546546 Clustering
Transitivity Clustering 0.0 T=0.5570375206493683 Clustering