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=298
samples=20
Clustering
Self Organizing Maps 0.0 x=293
y=213
Clustering
Spectral Clustering 0.014 k=24 Clustering
clusterdp 0.072 k=24
dc=3.6781585066443236
Clustering
HDBSCAN 0.0 minPts=19
k=151
Clustering
AGNES 0.0 method=single
metric=euclidean
k=292
Clustering
c-Means 0.0 k=342
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=345 Clustering
DIANA 0.0 metric=euclidean
k=156
Clustering
DBSCAN 0.0 eps=7.356317013288647
MinPts=332
Clustering
Hierarchical Clustering 0.0 method=single
k=361
Clustering
fanny 0.0 k=123
membexp=2.0
Clustering
k-Means 0.0 k=195
nstart=10
Clustering
DensityCut 0.192 alpha=0.15873015762144138
K=7
Clustering
clusterONE 0.753 s=345
d=0.26666666666666666
Clustering
Affinity Propagation 0.06 dampfact=0.845
preference=27.586188799832428
maxits=5000
convits=200
Clustering
Markov Clustering 0.753 I=5.474274274274276 Clustering
Transitivity Clustering 0.0 T=36.30294582133437 Clustering
MCODE 0.043 v=0.1
cutoff=32.183886933137835
haircut=T
fluff=T
Clustering