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=399
y=359
Clustering
Spectral Clustering 0.014 k=24 Clustering
clusterdp 0.072 k=24
dc=3.6781585066443236
Clustering
HDBSCAN 0.0 minPts=24
k=194
Clustering
AGNES 0.0 method=single
metric=euclidean
k=301
Clustering
c-Means 0.0 k=342
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=313 Clustering
DIANA 0.0 metric=euclidean
k=377
Clustering
DBSCAN 0.0 eps=2.4521056710962155
MinPts=372
Clustering
Hierarchical Clustering 0.0 method=single
k=208
Clustering
fanny 0.0 k=119
membexp=1.1
Clustering
k-Means 0.0 k=192
nstart=10
Clustering
DensityCut 0.192 alpha=0.1624503968253968
K=12
Clustering
clusterONE 0.753 s=372
d=0.7333333333333333
Clustering
Affinity Propagation 0.06 dampfact=0.845
preference=27.586188799832428
maxits=3500
convits=275
Clustering
Markov Clustering 0.753 I=5.144644644644645 Clustering
Transitivity Clustering 0.0 T=36.15567220745471 Clustering
MCODE 0.043 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=F
Clustering