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=521
samples=20
Clustering
Self Organizing Maps 0.0 x=600
y=600
Clustering
Spectral Clustering 0.013 k=39 Clustering
clusterdp 0.003 k=17
dc=0.9295510122873538
Clustering
HDBSCAN 0.0 minPts=36
k=301
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=556
Clustering
c-Means 0.0 k=600
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=469 Clustering
DIANA 0.0 metric=euclidean
k=530
Clustering
DBSCAN 0.0 eps=0.4647755061436769
MinPts=280
Clustering
Hierarchical Clustering 0.0 method=single
k=509
Clustering
fanny 0.0 k=268
membexp=2.0
Clustering
k-Means 0.0 k=393
nstart=10
Clustering
DensityCut 0.007 alpha=0.4255952380952381
K=26
Clustering
clusterONE 0.935 s=380
d=0.0
Clustering
Affinity Propagation 0.004 dampfact=0.7725
preference=10.457448888232731
maxits=2000
convits=275
Clustering
Markov Clustering 0.935 I=8.280580580580581 Clustering
Transitivity Clustering 0.0 T=13.929307961903591 Clustering
MCODE 0.017 v=0.4
cutoff=12.781326418951116
haircut=T
fluff=T
Clustering