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 0.375 x=335
y=4666
Clustering
Spectral Clustering 0.85 k=42 Clustering
clusterdp 0.855 k=23
dc=36008.34461886732
Clustering
HDBSCAN 0.611 minPts=1
k=2093
Clustering
AGNES 0.822 method=ward
metric=euclidean
k=11
Clustering
c-Means 0.847 k=16
m=1.01
Clustering
k-Medoids (PAM) 0.844 k=17 Clustering
DIANA 0.767 metric=euclidean
k=16
Clustering
DBSCAN 0.63 eps=504116.8246641425
MinPts=3833
Clustering
Hierarchical Clustering 0.79 method=complete
k=17
Clustering
fanny 0.84 k=17
membexp=2.0
Clustering
k-Means 0.844 k=47
nstart=10
Clustering
DensityCut 0.861 alpha=0.9877929687500002
K=121
Clustering
clusterONE 0.125 s=1
d=0.6666666666666666
Clustering
Affinity Propagation 0.547 dampfact=0.99
preference=0.0
maxits=4250
convits=425
Clustering
Markov Clustering 0.125 I=3.0955955955955954 Clustering
Transitivity Clustering 0.835 T=967791.8448614491 Clustering
MCODE 0.347 v=0.0
cutoff=990229.4770188513
haircut=T
fluff=F
Clustering