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=619
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=735
Clustering
Spectral Clustering 0.006 k=62 Clustering
clusterdp 0.0 k=12
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=105
k=683
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=634
Clustering
c-Means 0.0 k=748
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=786 Clustering
DIANA 0.0 metric=euclidean
k=494
Clustering
DBSCAN 0.0 eps=1.293848694571527
MinPts=683
Clustering
Hierarchical Clustering 0.0 method=single
k=735
Clustering
fanny 0.0 k=200
membexp=2.0
Clustering
k-Means 0.0 k=266
nstart=10
Clustering
DensityCut 0.0 alpha=0.0
K=13
Clustering
clusterONE 0.783 s=446
d=0.8
Clustering
Affinity Propagation 0.002 dampfact=0.99
preference=0.0
maxits=5000
convits=425
Clustering
Markov Clustering 0.783 I=7.184784784784785 Clustering
Transitivity Clustering 0.0 T=37.72754001288147 Clustering
MCODE 0.001 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering