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 0.69 metric=euclidean
k=3
samples=20
Clustering
Self Organizing Maps 0.457 x=2
y=1
Clustering
Spectral Clustering 0.545 k=20 Clustering
clusterdp 0.827 k=21
dc=17.164739697673507
Clustering
HDBSCAN 0.92 minPts=2
k=56
Clustering
AGNES 0.92 method=complete
metric=euclidean
k=56
Clustering
c-Means 0.73 k=4
m=1.01
Clustering
k-Medoids (PAM) 0.69 k=3 Clustering
DIANA 0.713 metric=euclidean
k=6
Clustering
DBSCAN 0.895 eps=17.164739697673507
MinPts=292
Clustering
Hierarchical Clustering 0.92 method=single
k=57
Clustering
fanny 0.692 k=17
membexp=5.0
Clustering
k-Means 0.69 k=5
nstart=10
Clustering
DensityCut 0.807 alpha=0.16338045634920634
K=7
Clustering
clusterONE 0.247 s=27
d=0.8666666666666667
Clustering
Affinity Propagation 0.305 dampfact=0.99
preference=0.0
maxits=3500
convits=425
Clustering
Markov Clustering 0.247 I=3.1757757757757763 Clustering
Transitivity Clustering 0.782 T=30.08063563491904 Clustering
MCODE 0.663 v=0.5
cutoff=29.11875484426756
haircut=F
fluff=T
Clustering