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=676
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=735
Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=18
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=79
k=525
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=394
Clustering
c-Means 0.0 k=375
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=776 Clustering
DIANA 0.0 metric=euclidean
k=483
Clustering
DBSCAN 0.0 eps=0.0
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=complete
k=577
Clustering
fanny 0.0 k=146
membexp=2.0
Clustering
k-Means 0.0 k=486
nstart=10
Clustering
DensityCut 0.0 alpha=0.0
K=13
Clustering
clusterONE 1.0 s=656
d=0.26666666666666666
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=38.815460837145814
maxits=3500
convits=350
Clustering
Markov Clustering 1.0 I=2.507607607607608 Clustering
Transitivity Clustering 0.0 T=37.72754001288147 Clustering
MCODE 0.0 v=0.9
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering