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=614
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=604
Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=14
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=132
k=788
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=768
Clustering
c-Means 0.0 k=502
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=668 Clustering
DIANA 0.0 metric=euclidean
k=521
Clustering
DBSCAN 0.0 eps=0.0
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=complete
k=326
Clustering
fanny 0.0 k=269
membexp=5.0
Clustering
k-Means 0.0 k=361
nstart=10
Clustering
DensityCut 0.0 alpha=1.52587890625E-5
K=10
Clustering
clusterONE 1.0 s=525
d=0.2
Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=38.815460837145814
maxits=5000
convits=200
Clustering
Markov Clustering 1.0 I=1.1623623623623625 Clustering
Transitivity Clustering 0.0 T=37.76639432803376 Clustering
MCODE 0.0 v=0.9
cutoff=35.58083910071699
haircut=F
fluff=T
Clustering