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 1.0 metric=euclidean
k=2
samples=20
Clustering
Self Organizing Maps 0.798 x=2
y=1
Clustering
Spectral Clustering 0.815 k=2 Clustering
clusterdp 0.994 k=2
dc=14.647952075290254
Clustering
HDBSCAN 1.0 minPts=80
k=1
Clustering
AGNES 1.0 method=average
metric=euclidean
k=4
Clustering
c-Means 0.798 k=2
m=1.5
Clustering
k-Medoids (PAM) 0.798 k=2 Clustering
DIANA 1.0 metric=euclidean
k=7
Clustering
DBSCAN 1.0 eps=12.694891798584885
MinPts=70
Clustering
Hierarchical Clustering 0.994 method=complete
k=2
Clustering
fanny 0.798 k=3
membexp=1.1
Clustering
k-Means 0.798 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.42857142857142855
K=43
Clustering
clusterONE 1.0 s=1
d=0.06666666666666667
Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=0.0
maxits=3500
convits=200
Clustering
Markov Clustering 1.0 I=1.411811811811812 Clustering
Transitivity Clustering 1.0 T=7.2140064274702755 Clustering