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=28
samples=20
Clustering
Self Organizing Maps 0.465 x=2
y=2
Clustering
Spectral Clustering 0.002 k=11 Clustering
clusterdp 0.0 k=34
dc=0.08135679577905247
Clustering
HDBSCAN 0.0 minPts=16
k=30
Clustering
AGNES 0.013 method=average
metric=euclidean
k=11
Clustering
c-Means 0.258 k=3
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=12 Clustering
DIANA 0.016 metric=euclidean
k=20
Clustering
DBSCAN 0.0 eps=0.0
MinPts=35
Clustering
Hierarchical Clustering 0.0 method=complete
k=2
Clustering
fanny 0.018 k=7
membexp=2.0
Clustering
k-Means 0.004 k=21
nstart=10
Clustering
DensityCut 0.127 alpha=0.43333333333333335
K=2
Clustering
clusterONE 1.0 s=1
d=0.3
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=0.0
maxits=2000
convits=350
Clustering
Markov Clustering 1.0 I=1.2247247247247248 Clustering
Transitivity Clustering 0.0 T=0.26324909144723435 Clustering
MCODE 1.0 v=0.0
cutoff=0.0
haircut=T
fluff=T
Clustering