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=274
samples=20
Clustering
Self Organizing Maps 0.0 x=385
y=239
Clustering
Spectral Clustering 0.014 k=24 Clustering
clusterdp 0.072 k=24
dc=3.6781585066443236
Clustering
HDBSCAN 0.0 minPts=7
k=79
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=243
Clustering
c-Means 0.0 k=374
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=337 Clustering
DIANA 0.0 metric=euclidean
k=374
Clustering
DBSCAN 0.0 eps=8.582369848836754
MinPts=306
Clustering
Hierarchical Clustering 0.0 method=complete
k=70
Clustering
fanny 0.0 k=103
membexp=5.0
Clustering
k-Means 0.0 k=267
nstart=10
Clustering
DensityCut 0.192 alpha=0.15341553287981857
K=5
Clustering
clusterONE 0.753 s=80
d=0.5
Clustering
Affinity Propagation 0.06 dampfact=0.845
preference=27.586188799832428
maxits=5000
convits=200
Clustering
Markov Clustering 0.753 I=5.545545545545545 Clustering
Transitivity Clustering 0.0 T=34.977483296417496 Clustering
MCODE 0.043 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=F
Clustering