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=85
samples=20
Clustering
Self Organizing Maps 0.0 x=250
y=233
Clustering
Spectral Clustering 0.0 k=53 Clustering
clusterdp 0.0 k=16
dc=0.8832000000000001
Clustering
HDBSCAN 0.0 minPts=20
k=25
Clustering
AGNES 0.0 method=complete
metric=euclidean
k=213
Clustering
c-Means 0.0 k=237
m=1.5
Clustering
k-Medoids (PAM) 0.0 k=144 Clustering
DIANA 0.0 metric=euclidean
k=181
Clustering
DBSCAN 0.0 eps=2.4288000000000003
MinPts=183
Clustering
Hierarchical Clustering 0.0 method=average
k=243
Clustering
fanny 0.0 k=90
membexp=5.0
Clustering
k-Means 0.0 k=183
nstart=10
Clustering
DensityCut 0.0 alpha=0.3357142857142857
K=5
Clustering
clusterONE 0.502 s=34
d=0.1
Clustering
Affinity Propagation 0.062 dampfact=0.9175
preference=2.484
maxits=4250
convits=500
Clustering
Markov Clustering 0.502 I=5.42082082082082 Clustering
Transitivity Clustering 0.0 T=3.1661261261261266 Clustering
MCODE 0.021 v=0.6
cutoff=3.036
haircut=F
fluff=T
Clustering