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 0.0 metric=euclidean
k=188
samples=20
Clustering
Self Organizing Maps 0.0 x=160
y=200
Clustering
Spectral Clustering 0.004 k=59 Clustering
clusterdp 0.022 k=6
dc=5.385181681800475
Clustering
HDBSCAN 0.0 minPts=162
k=200
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=190
Clustering
c-Means 0.0 k=88
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=194 Clustering
DIANA 0.0 metric=euclidean
k=194
Clustering
DBSCAN 0.0 eps=7.343429566091556
MinPts=34
Clustering
Hierarchical Clustering 0.0 method=complete
k=184
Clustering
fanny 0.0 k=21
membexp=7.033333333333333
Clustering
k-Means 0.0 k=193
nstart=10
Clustering
DensityCut 0.083 alpha=0.0
K=2
Clustering
clusterONE 0.006 s=3
d=0.7
Clustering
Markov Clustering 1.0 I=9.465465465465465 Clustering
Transitivity Clustering 0.0 T=13.216703062895514 Clustering
MCODE 0.052 v=0.1
cutoff=4.895619710727704
haircut=T
fluff=T
Clustering