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 0.845 metric=euclidean
k=29
samples=20
Clustering
Self Organizing Maps 0.406 x=2
y=1
Clustering
Spectral Clustering 0.839 k=42 Clustering
clusterdp 0.853 k=22
dc=36008.34461886732
Clustering
HDBSCAN 0.565 minPts=92
k=2054
Clustering
AGNES 0.819 method=ward
metric=euclidean
k=11
Clustering
c-Means 0.84 k=16
m=1.01
Clustering
k-Medoids (PAM) 0.831 k=17 Clustering
DIANA 0.769 metric=euclidean
k=16
Clustering
DBSCAN 0.694 eps=576133.5139018771
MinPts=4500
Clustering
Hierarchical Clustering 0.794 method=average
k=17
Clustering
fanny 0.827 k=17
membexp=2.0
Clustering
k-Means 0.834 k=47
nstart=10
Clustering
DensityCut 0.861 alpha=0.9877929687500002
K=121
Clustering
clusterONE 0.263 s=1
d=0.6666666666666666
Clustering
Affinity Propagation 0.442 dampfact=0.99
preference=0.0
maxits=4250
convits=425
Clustering
Markov Clustering 0.263 I=3.0955955955955954 Clustering
Transitivity Clustering 0.82 T=967791.8448614491 Clustering
MCODE 0.446 v=0.0
cutoff=990229.4770188513
haircut=T
fluff=F
Clustering