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=32
samples=20
Clustering
Self Organizing Maps 0.0 x=28
y=38
Clustering
Spectral Clustering 0.488 k=26 Clustering
clusterdp 0.0 k=5
dc=0.36610558100573615
Clustering
HDBSCAN 0.0 minPts=11
k=30
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=37
Clustering
c-Means 0.0 k=33
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=27 Clustering
DIANA 0.0 metric=euclidean
k=36
Clustering
DBSCAN 0.0 eps=0.2033919894476312
MinPts=8
Clustering
Hierarchical Clustering 0.0 method=complete
k=32
Clustering
fanny 0.065 k=16
membexp=1.1
Clustering
k-Means 0.0 k=36
nstart=10
Clustering
DensityCut 0.23 alpha=0.8373015873015873
K=2
Clustering
clusterONE 0.18 s=8
d=0.7666666666666667
Clustering
Affinity Propagation 0.057 dampfact=0.845
preference=0.45763197625717017
maxits=4250
convits=350
Clustering
Markov Clustering 0.369 I=9.955455455455455 Clustering
Transitivity Clustering 0.0 T=0.48740783056819725 Clustering