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=273
samples=20
Clustering
Self Organizing Maps 0.0 x=131
y=120
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=21
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=28
k=53
Clustering
AGNES 0.0 method=ward
metric=euclidean
k=259
Clustering
c-Means 0.0 k=263
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=250 Clustering
DIANA 0.0 metric=euclidean
k=91
Clustering
DBSCAN 0.0 eps=2.9295904150580507
MinPts=250
Clustering
Hierarchical Clustering 0.0 method=average
k=237
Clustering
fanny 0.0 k=99
membexp=5.0
Clustering
k-Means 0.0 k=233
nstart=10
Clustering
DensityCut 0.005 alpha=0.06914682539682541
K=2
Clustering
clusterONE 0.667 s=70
d=0.4
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=4250
convits=200
Clustering
Markov Clustering 0.471 I=9.866366366366366 Clustering
Transitivity Clustering 0.0 T=27.888293140342405 Clustering