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=37
samples=20
Clustering
Self Organizing Maps 0.0 x=33
y=301
Clustering
Spectral Clustering 0.0 k=37 Clustering
clusterdp 0.0 k=17
dc=30.307754783223388
Clustering
HDBSCAN 0.0 minPts=5
k=36
Clustering
AGNES 0.0 method=average
metric=euclidean
k=228
Clustering
c-Means 0.0 k=205
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=306 Clustering
DIANA 0.0 metric=euclidean
k=115
Clustering
DBSCAN 0.0 eps=5.051292463870565
MinPts=301
Clustering
Hierarchical Clustering 0.0 method=single
k=119
Clustering
fanny 0.0 k=97
membexp=2.0
Clustering
k-Means 0.0 k=104
nstart=10
Clustering
DensityCut 0.0 alpha=0.0547406462585034
K=10
Clustering
clusterONE 0.669 s=312
d=0.8333333333333334
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=15.153877391611694
maxits=4250
convits=425
Clustering
Markov Clustering 0.669 I=2.008708708708709 Clustering
Transitivity Clustering 0.0 T=30.06505004021459 Clustering
MCODE 0.006 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T
Clustering