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=233
samples=20
Clustering
Self Organizing Maps 1.0 x=43
y=225
Clustering
Spectral Clustering 1.0 k=34 Clustering
clusterdp 1.0 k=2
dc=0.44160000000000005
Clustering
HDBSCAN 1.0 minPts=48
k=250
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=177
Clustering
c-Means 1.0 k=9
m=2.25
Clustering
k-Medoids (PAM) 1.0 k=84 Clustering
DIANA 1.0 metric=euclidean
k=89
Clustering
DBSCAN 1.0 eps=0.9936000000000001
MinPts=225
Clustering
Hierarchical Clustering 1.0 method=single
k=120
Clustering
fanny 1.0 k=96
membexp=2.0
Clustering
k-Means 1.0 k=96
nstart=10
Clustering
DensityCut 1.0 alpha=0.035713996206011074
K=4
Clustering
clusterONE 0.0 s=250
d=0.1
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=3.3120000000000003
maxits=3500
convits=200
Clustering
Markov Clustering 0.5 I=9.973273273273273 Clustering
Transitivity Clustering 1.0 T=3.0467747747747747 Clustering
MCODE 0.999 v=0.9
cutoff=3.036
haircut=F
fluff=F
Clustering