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 0.232 metric=euclidean
k=196
samples=20
Clustering
Self Organizing Maps 0.338 x=2
y=140
Clustering
Spectral Clustering 0.782 k=4 Clustering
clusterdp 0.17 k=20
dc=0.0
Clustering
HDBSCAN 0.231 minPts=171
k=200
Clustering
AGNES 0.509 method=complete
metric=euclidean
k=2
Clustering
c-Means 0.808 k=2
m=5.0
Clustering
k-Medoids (PAM) 0.232 k=198 Clustering
DIANA 0.738 metric=euclidean
k=47
Clustering
DBSCAN 0.231 eps=1.8210053077346027
MinPts=54
Clustering
Hierarchical Clustering 0.509 method=single
k=2
Clustering
fanny 0.606 k=21
membexp=8.516666666666667
Clustering
k-Means 0.782 k=2
nstart=10
Clustering
DensityCut 0.081 alpha=0.4583333333333333
K=3
Clustering
clusterONE 0.364 s=4
d=0.1
Clustering
Markov Clustering 0.0 I=1.117817817817818 Clustering
Transitivity Clustering 0.294 T=4.520613776958774 Clustering
MCODE 0.152 v=0.2
cutoff=4.552513269336507
haircut=F
fluff=T
Clustering