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=1
samples=20
Clustering
Self Organizing Maps 0.496 x=2
y=1
Clustering
Spectral Clustering 0.499 k=3 Clustering
clusterdp 1.0 k=2
dc=3.2016
Clustering
HDBSCAN 1.0 minPts=24
k=1
Clustering
AGNES 1.0 method=single
metric=euclidean
k=1
Clustering
c-Means 0.496 k=2
m=1.5
Clustering
k-Medoids (PAM) 0.496 k=2 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=2.7600000000000002
MinPts=50
Clustering
Hierarchical Clustering 1.0 method=average
k=2
Clustering
fanny 1.0 k=2
membexp=1.1
Clustering
k-Means 0.496 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.3333333333333333
K=12
Clustering
clusterONE 1.0 s=34
d=0.1
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 1.0 I=4.592292292292293 Clustering
Transitivity Clustering 1.0 T=0.5171891891891892 Clustering
MCODE 0.778 v=0.2
cutoff=1.2420000000000002
haircut=T
fluff=T
Clustering