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=253
samples=20
Clustering
Self Organizing Maps 0.0 x=31
y=240
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=24
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=40
k=290
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=267
Clustering
c-Means 0.0 k=140
m=1.01
Clustering
k-Medoids (PAM) 0.0 k=98 Clustering
DIANA 0.0 metric=euclidean
k=245
Clustering
DBSCAN 0.0 eps=0.9765301383526837
MinPts=50
Clustering
Hierarchical Clustering 0.0 method=average
k=137
Clustering
fanny 0.0 k=99
membexp=2.0
Clustering
k-Means 0.0 k=284
nstart=10
Clustering
DensityCut 0.005 alpha=0.1040107709750567
K=2
Clustering
clusterONE 0.667 s=300
d=0.8
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=29.29590415058051
maxits=3500
convits=425
Clustering
Markov Clustering 0.471 I=9.973273273273273 Clustering
Transitivity Clustering 0.0 T=28.15222020476205 Clustering