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=186
samples=20
Clustering
Self Organizing Maps 0.0 x=312
y=249
Clustering
Spectral Clustering 0.0 k=59 Clustering
clusterdp 0.0 k=11
dc=12.123101913289355
Clustering
HDBSCAN 0.0 minPts=5
k=65
Clustering
AGNES 0.0 method=average
metric=euclidean
k=262
Clustering
c-Means 0.0 k=142
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=102 Clustering
DIANA 0.0 metric=euclidean
k=252
Clustering
DBSCAN 0.0 eps=0.0
MinPts=11
Clustering
Hierarchical Clustering 0.0 method=complete
k=158
Clustering
fanny 0.0 k=111
membexp=1.1
Clustering
k-Means 0.0 k=138
nstart=10
Clustering
DensityCut 0.0 alpha=0.05673363095238094
K=6
Clustering
clusterONE 1.0 s=42
d=0.0
Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=15.153877391611694
maxits=2000
convits=500
Clustering
Markov Clustering 1.0 I=9.5990990990991 Clustering
Transitivity Clustering 0.0 T=26.06042178056946 Clustering
MCODE 0.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T
Clustering