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=214
samples=20
Clustering
Self Organizing Maps 0.0 x=167
y=1
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=11
dc=0.7728
Clustering
HDBSCAN 0.0 minPts=12
k=238
Clustering
AGNES 0.0 method=single
metric=euclidean
k=55
Clustering
c-Means 0.0 k=177
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=123 Clustering
DIANA 0.0 metric=euclidean
k=246
Clustering
DBSCAN 0.0 eps=1.7664000000000002
MinPts=191
Clustering
Hierarchical Clustering 0.0 method=complete
k=106
Clustering
fanny 0.0 k=97
membexp=1.1
Clustering
k-Means 0.0 k=74
nstart=10
Clustering
DensityCut 0.0 alpha=0.369047619047619
K=5
Clustering
clusterONE 0.502 s=167
d=0.16666666666666666
Clustering
Affinity Propagation 0.062 dampfact=0.845
preference=2.484
maxits=3500
convits=500
Clustering
Markov Clustering 0.502 I=4.93083083083083 Clustering
Transitivity Clustering 0.0 T=3.0202522522522526 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering