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 0.83 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.676 x=2
y=1
Clustering
Spectral Clustering 0.727 k=20 Clustering
clusterdp 0.906 k=21
dc=17.164739697673507
Clustering
HDBSCAN 0.959 minPts=2
k=56
Clustering
AGNES 0.959 method=complete
metric=euclidean
k=56
Clustering
c-Means 0.854 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.83 k=3 Clustering
DIANA 0.833 metric=euclidean
k=6
Clustering
DBSCAN 0.945 eps=17.164739697673507
MinPts=292
Clustering
Hierarchical Clustering 0.959 method=single
k=57
Clustering
fanny 0.83 k=3
membexp=1.1
Clustering
k-Means 0.83 k=5
nstart=10
Clustering
DensityCut 0.898 alpha=0.16338045634920634
K=7
Clustering
clusterONE 0.497 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.522 dampfact=0.7
preference=9.195396266610809
maxits=3500
convits=425
Clustering
Markov Clustering 0.497 I=3.1757757757757763 Clustering
Transitivity Clustering 0.88 T=30.08063563491904 Clustering
MCODE 0.798 v=0.5
cutoff=29.11875484426756
haircut=F
fluff=T
Clustering