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=192
samples=20
Clustering
Self Organizing Maps 0.0 x=121
y=30
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=23
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=300
k=230
Clustering
AGNES 0.0 method=average
metric=euclidean
k=241
Clustering
c-Means 0.0 k=64
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=196 Clustering
DIANA 0.0 metric=euclidean
k=217
Clustering
DBSCAN 0.0 eps=0.9765301383526837
MinPts=50
Clustering
Hierarchical Clustering 0.0 method=complete
k=224
Clustering
fanny 0.0 k=127
membexp=5.0
Clustering
k-Means 0.0 k=247
nstart=10
Clustering
DensityCut 0.0 alpha=0.06914682539682541
K=2
Clustering
clusterONE 1.0 s=190
d=0.9
Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=5000
convits=350
Clustering
Markov Clustering 0.352 I=9.608008008008008 Clustering
Transitivity Clustering 0.0 T=28.034919287242207 Clustering