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=187
samples=20
Clustering
Self Organizing Maps 0.0 x=173
y=34
Clustering
Spectral Clustering 0.004 k=59 Clustering
clusterdp 0.022 k=5
dc=4.895619710727704
Clustering
HDBSCAN 0.0 minPts=114
k=200
Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=175
Clustering
c-Means 0.0 k=31
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=194 Clustering
DIANA 0.0 metric=euclidean
k=191
Clustering
DBSCAN 0.0 eps=11.74948730574649
MinPts=14
Clustering
Hierarchical Clustering 0.0 method=single
k=196
Clustering
fanny 0.0 k=48
membexp=3.7700000000000005
Clustering
k-Means 0.0 k=186
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=2.7125125125125127 Clustering
Transitivity Clustering 0.0 T=13.687153005067545 Clustering
MCODE 0.052 v=0.1
cutoff=4.895619710727704
haircut=T
fluff=T
Clustering