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=217
samples=20
Clustering
Self Organizing Maps 0.0 x=250
y=250
Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=22
dc=1.7664000000000002
Clustering
HDBSCAN 0.0 minPts=12
k=238
Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=22
Clustering
c-Means 0.0 k=232
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=54 Clustering
DIANA 0.0 metric=euclidean
k=87
Clustering
DBSCAN 0.0 eps=2.4288000000000003
MinPts=183
Clustering
Hierarchical Clustering 0.0 method=average
k=218
Clustering
fanny 0.0 k=91
membexp=5.0
Clustering
k-Means 0.0 k=197
nstart=10
Clustering
DensityCut 0.0 alpha=0.03334263392857141
K=5
Clustering
clusterONE 0.502 s=133
d=0.5
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=7.238238238238238 Clustering
Transitivity Clustering 0.0 T=3.245693693693694 Clustering
MCODE 0.021 v=0.8
cutoff=3.036
haircut=F
fluff=T
Clustering