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 0.842 metric=euclidean
k=8
samples=20
Clustering
Self Organizing Maps 0.615 x=2
y=27
Clustering
Spectral Clustering 0.947 k=8 Clustering
clusterdp 1.0 k=8
dc=2.587697389143054
Clustering
HDBSCAN 0.9 minPts=8
k=95
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=4
Clustering
c-Means 0.871 k=8
m=3.5
Clustering
k-Medoids (PAM) 0.838 k=4 Clustering
DIANA 0.839 metric=euclidean
k=52
Clustering
DBSCAN 0.865 eps=32.34621736428818
MinPts=604
Clustering
Hierarchical Clustering 0.986 method=single
k=6
Clustering
fanny 0.845 k=4
membexp=1.1
Clustering
k-Means 0.836 k=6
nstart=10
Clustering
DensityCut 1.0 alpha=1.52587890625E-5
K=10
Clustering
clusterONE 0.465 s=368
d=0.6333333333333333
Clustering
Affinity Propagation 0.48 dampfact=0.99
preference=0.0
maxits=3500
convits=350
Clustering
Markov Clustering 0.465 I=1.1 Clustering
Transitivity Clustering 0.99 T=28.8299018430052 Clustering
MCODE 0.821 v=0.3
cutoff=30.728906496073773
haircut=F
fluff=F
Clustering