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 0.01 metric=euclidean
k=784
samples=20
Clustering
Self Organizing Maps 0.409 x=630
y=263
Clustering
Spectral Clustering 0.352 k=9 Clustering
clusterdp 0.334 k=8
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=713
k=788
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=788
Clustering
c-Means 0.0 k=462
m=5.0
Clustering
k-Medoids (PAM) 0.006 k=787 Clustering
DIANA 0.0 metric=euclidean
k=786
Clustering
DBSCAN 0.0 eps=0.0
MinPts=525
Clustering
Hierarchical Clustering 0.0 method=complete
k=788
Clustering
fanny 0.0 k=196
membexp=5.0
Clustering
k-Means 0.009 k=786
nstart=10
Clustering
DensityCut 0.334 alpha=0.011160714285714286
K=9
Clustering
clusterONE Infinity s=27
d=0.8333333333333334
Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=38.815460837145814
maxits=2750
convits=425
Clustering
Markov Clustering Infinity I=1.6612612612612614 Clustering
Transitivity Clustering 0.0 T=38.815460837145814 Clustering
MCODE 0.506 v=0.2
cutoff=32.34621736428818
haircut=F
fluff=T
Clustering