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=154
samples=20
Clustering
Self Organizing Maps 0.0 x=300
y=210
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=23
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=57
k=257
Clustering
AGNES 0.0 method=single
metric=euclidean
k=270
Clustering
c-Means 0.0 k=296
m=5.0
Clustering
k-Medoids (PAM) 0.0 k=155 Clustering
DIANA 0.0 metric=euclidean
k=245
Clustering
DBSCAN 0.0 eps=0.9765301383526837
MinPts=50
Clustering
Hierarchical Clustering 0.0 method=single
k=110
Clustering
fanny 0.0 k=141
membexp=2.0
Clustering
k-Means 0.0 k=286
nstart=10
Clustering
DensityCut 0.0 alpha=0.06914682539682541
K=2
Clustering
clusterONE 1.0 s=260
d=0.03333333333333333
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=29.29590415058051
maxits=2750
convits=200
Clustering
Markov Clustering 0.352 I=9.073473473473474 Clustering
Transitivity Clustering 0.0 T=28.562773416081495 Clustering