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=303
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=735
Clustering
Spectral Clustering 0.006 k=62 Clustering
clusterdp 0.0 k=17
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=188
k=675
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=624
Clustering
c-Means 0.0 k=248
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=715 Clustering
DIANA 0.0 metric=euclidean
k=516
Clustering
DBSCAN 0.0 eps=3.881546083714581
MinPts=630
Clustering
Hierarchical Clustering 0.0 method=single
k=558
Clustering
fanny 0.0 k=226
membexp=1.1
Clustering
k-Means 0.0 k=230
nstart=10
Clustering
DensityCut 0.0 alpha=0.0015625
K=10
Clustering
clusterONE 0.783 s=132
d=0.5
Clustering
Affinity Propagation 0.002 dampfact=0.9175
preference=9.703865209286453
maxits=3500
convits=425
Clustering
Markov Clustering 0.783 I=4.137937937937938 Clustering
Transitivity Clustering 0.0 T=34.81346637645911 Clustering
MCODE 0.001 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering