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=23
samples=20
Clustering
Self Organizing Maps 0.0 x=34
y=10
Clustering
Spectral Clustering 0.488 k=26 Clustering
clusterdp 0.0 k=22
dc=0.2033919894476312
Clustering
HDBSCAN 0.0 minPts=30
k=36
Clustering
AGNES 0.0 method=average
metric=euclidean
k=30
Clustering
c-Means 0.0 k=36
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=34 Clustering
DIANA 0.0 metric=euclidean
k=30
Clustering
DBSCAN 0.0 eps=0.2033919894476312
MinPts=8
Clustering
Hierarchical Clustering 0.0 method=average
k=35
Clustering
fanny 0.065 k=16
membexp=1.1
Clustering
k-Means 0.0 k=35
nstart=10
Clustering
DensityCut 0.23 alpha=0.7071428571428572
K=2
Clustering
clusterONE 0.18 s=7
d=0.8
Clustering
Affinity Propagation 0.057 dampfact=0.7
preference=0.45763197625717017
maxits=3500
convits=425
Clustering
Markov Clustering 0.369 I=9.955455455455455 Clustering
Transitivity Clustering 0.0 T=0.48740783056819725 Clustering