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=53
samples=20
Clustering
Self Organizing Maps 0.0 x=175
y=225
Clustering
Spectral Clustering 0.004 k=25 Clustering
clusterdp 0.0 k=23
dc=0.9403135476894363
Clustering
HDBSCAN 0.0 minPts=190
k=250
Clustering
AGNES 0.0 method=single
metric=euclidean
k=55
Clustering
c-Means 0.0 k=97
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=51 Clustering
DIANA 0.0 metric=euclidean
k=83
Clustering
DBSCAN 0.0 eps=1.5149496046107584
MinPts=183
Clustering
Hierarchical Clustering 0.0 method=single
k=75
Clustering
fanny 0.0 k=11
membexp=5.0
Clustering
k-Means 0.0 k=84
nstart=10
Clustering
DensityCut 0.0 alpha=0.04761718568347749
K=11
Clustering
clusterONE 1.0 s=216
d=0.6666666666666666
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.7835946230745302
maxits=4250
convits=275
Clustering
Markov Clustering 1.0 I=5.492092092092093 Clustering
Transitivity Clustering 0.0 T=1.1279370049861606 Clustering
MCODE 0.0 v=0.4
cutoff=1.2406914865346728
haircut=F
fluff=T
Clustering