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 1.0 metric=euclidean
k=161
samples=20
Clustering
Self Organizing Maps 1.0 x=68
y=233
Clustering
Spectral Clustering 1.0 k=24 Clustering
clusterdp 1.0 k=21
dc=2.208
Clustering
HDBSCAN 1.0 minPts=238
k=202
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=246
Clustering
c-Means 1.0 k=177
m=1.01
Clustering
k-Medoids (PAM) 1.0 k=85 Clustering
DIANA 1.0 metric=euclidean
k=137
Clustering
DBSCAN 1.0 eps=0.0
MinPts=42
Clustering
Hierarchical Clustering 1.0 method=complete
k=63
Clustering
fanny 1.0 k=75
membexp=2.0
Clustering
k-Means 1.0 k=210
nstart=10
Clustering
DensityCut 1.0 alpha=0.03214285714285714
K=7
Clustering
clusterONE 0.0 s=191
d=0.23333333333333334
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=3.3120000000000003
maxits=2750
convits=200
Clustering
Markov Clustering 0.5 I=9.44764764764765 Clustering
Transitivity Clustering 1.0 T=3.1462342342342344 Clustering
MCODE 0.999 v=0.9
cutoff=3.036
haircut=F
fluff=F
Clustering