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=28
samples=20
Clustering
Self Organizing Maps 0.535 x=2
y=2
Clustering
Spectral Clustering 0.998 k=11 Clustering
clusterdp 1.0 k=34
dc=0.08135679577905247
Clustering
HDBSCAN 1.0 minPts=16
k=30
Clustering
AGNES 0.987 method=average
metric=euclidean
k=11
Clustering
c-Means 0.742 k=3
m=3.5
Clustering
k-Medoids (PAM) 1.0 k=12 Clustering
DIANA 0.984 metric=euclidean
k=20
Clustering
DBSCAN 1.0 eps=0.0
MinPts=35
Clustering
Hierarchical Clustering 1.0 method=complete
k=2
Clustering
fanny 0.982 k=7
membexp=2.0
Clustering
k-Means 0.996 k=21
nstart=10
Clustering
DensityCut 0.873 alpha=0.43333333333333335
K=2
Clustering
clusterONE 0.0 s=1
d=0.3
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering 0.0 I=1.2247247247247248 Clustering
Transitivity Clustering 1.0 T=0.26324909144723435 Clustering
MCODE 0.0 v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering