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 0.806 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.643 x=15
y=279
Clustering
Spectral Clustering 0.804 k=20 Clustering
clusterdp 0.873 k=6
dc=3.6781585066443236
Clustering
HDBSCAN 0.843 minPts=2
k=56
Clustering
AGNES 0.866 method=flexible
metric=euclidean
k=8
Clustering
c-Means 0.847 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.806 k=3 Clustering
DIANA 0.799 metric=euclidean
k=6
Clustering
DBSCAN 0.857 eps=35.555532230895125
MinPts=332
Clustering
Hierarchical Clustering 0.843 method=complete
k=6
Clustering
fanny 0.806 k=3
membexp=1.1
Clustering
k-Means 0.806 k=5
nstart=10
Clustering
DensityCut 0.912 alpha=0.16338045634920634
K=7
Clustering
clusterONE 0.0 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.696 dampfact=0.7
preference=9.195396266610809
maxits=3500
convits=425
Clustering
Markov Clustering 0.0 I=3.1757757757757763 Clustering
Transitivity Clustering 0.847 T=30.08063563491904 Clustering
MCODE 0.781 v=0.7
cutoff=29.11875484426756
haircut=T
fluff=F
Clustering