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=112
samples=20
Clustering
Self Organizing Maps 0.0 x=71
y=180
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=21
dc=0.9765301383526837
Clustering
HDBSCAN 0.0 minPts=20
k=270
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=61
Clustering
c-Means 0.0 k=236
m=3.5
Clustering
k-Medoids (PAM) 0.0 k=234 Clustering
DIANA 0.0 metric=euclidean
k=101
Clustering
DBSCAN 0.0 eps=0.9765301383526837
MinPts=50
Clustering
Hierarchical Clustering 0.0 method=average
k=213
Clustering
fanny 0.0 k=99
membexp=5.0
Clustering
k-Means 0.0 k=297
nstart=10
Clustering
DensityCut 0.005 alpha=0.1040107709750567
K=2
Clustering
clusterONE 0.667 s=50
d=0.16666666666666666
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=27.800317452202524 Clustering