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=1
samples=20
Clustering
Self Organizing Maps 1.0 x=2
y=2
Clustering
Spectral Clustering 1.0 k=5 Clustering
clusterdp 1.0 k=3
dc=0.1220351936685787
Clustering
HDBSCAN 1.0 minPts=8
k=1
Clustering
AGNES 1.0 method=average
metric=euclidean
k=1
Clustering
c-Means 0.89 k=3
m=3.5
Clustering
k-Medoids (PAM) 0.866 k=4 Clustering
DIANA 1.0 metric=euclidean
k=10
Clustering
DBSCAN 1.0 eps=0.0
MinPts=4
Clustering
Hierarchical Clustering 1.0 method=average
k=2
Clustering
fanny 1.0 k=7
membexp=5.0
Clustering
k-Means 1.0 k=5
nstart=10
Clustering
DensityCut 1.0 alpha=0.3333333333333333
K=2
Clustering
clusterONE 1.0 s=1
d=0.3
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering 1.0 I=1.2247247247247248 Clustering
Transitivity Clustering 1.0 T=0.03786877881607548 Clustering
MCODE 1.0 v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering