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 1.0 metric=euclidean
k=86
samples=20
Clustering
Self Organizing Maps 1.0 x=71
y=180
Clustering
Spectral Clustering 1.0 k=8 Clustering
clusterdp 1.0 k=23
dc=0.9765301383526837
Clustering
HDBSCAN 1.0 minPts=80
k=190
Clustering
AGNES 1.0 method=average
metric=euclidean
k=88
Clustering
c-Means 1.0 k=26
m=1.01
Clustering
k-Medoids (PAM) 1.0 k=102 Clustering
DIANA 1.0 metric=euclidean
k=64
Clustering
DBSCAN 1.0 eps=0.9765301383526837
MinPts=50
Clustering
Hierarchical Clustering 1.0 method=single
k=33
Clustering
fanny 1.0 k=99
membexp=2.0
Clustering
k-Means 1.0 k=109
nstart=10
Clustering
DensityCut 1.0 alpha=0.06914682539682541
K=2
Clustering
clusterONE 0.0 s=260
d=0.2
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=21.97192811293538
maxits=5000
convits=425
Clustering
Markov Clustering 0.648 I=9.403103103103104 Clustering
Transitivity Clustering 1.0 T=27.800317452202524 Clustering