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 0.858 metric=euclidean
k=41
samples=20
Clustering
Self Organizing Maps 0.98 x=2
y=1
Clustering
Spectral Clustering 0.97 k=2 Clustering
clusterdp 0.831 k=2
dc=0.0
Clustering
HDBSCAN 0.833 minPts=44
k=1
Clustering
AGNES 0.914 method=flexible
metric=euclidean
k=2
Clustering
c-Means 0.975 k=3
m=1.5
Clustering
k-Medoids (PAM) 0.858 k=4 Clustering
DIANA 0.97 metric=euclidean
k=3
Clustering
DBSCAN 0.833 eps=1.4686859132183112
MinPts=1
Clustering
Hierarchical Clustering 0.88 method=average
k=12
Clustering
fanny 0.975 k=2
membexp=1.99
Clustering
k-Means 0.975 k=3
nstart=10
Clustering
DensityCut 0.833 alpha=0.8095238095238095
K=29
Clustering
clusterONE 0.924 s=18
d=0.16666666666666666
Clustering
Markov Clustering 0.833 I=1.2336336336336338 Clustering
Transitivity Clustering 0.833 T=0.6174655491007915 Clustering
MCODE 0.833 v=0.0
cutoff=4.283667246886741
haircut=T
fluff=T
Clustering