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=430
samples=20
Clustering
Self Organizing Maps 0.0 x=101
y=40
Clustering
Spectral Clustering 0.0 k=100 Clustering
clusterdp 0.0 k=17
dc=0.9295510122873538
Clustering
HDBSCAN 0.0 minPts=143
k=257
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=585
Clustering
c-Means 0.0 k=68
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=598 Clustering
DIANA 0.0 metric=euclidean
k=472
Clustering
DBSCAN 0.0 eps=0.9295510122873538
MinPts=120
Clustering
Hierarchical Clustering 0.0 method=complete
k=421
Clustering
fanny 0.0 k=155
membexp=2.0
Clustering
k-Means 0.0 k=599
nstart=10
Clustering
DensityCut 0.0 alpha=0.38290550595238093
K=28
Clustering
clusterONE 1.0 s=340
d=0.16666666666666666
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=10.457448888232731
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=9.57237237237237 Clustering
Transitivity Clustering 0.0 T=13.88743629468344 Clustering
MCODE 0.001 v=0.8
cutoff=13.36229580163071
haircut=F
fluff=F
Clustering