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=8
samples=20
Clustering
Self Organizing Maps 0.987 x=2
y=1
Clustering
Spectral Clustering 1.0 k=12 Clustering
clusterdp 1.0 k=2
dc=7.4364080982988305
Clustering
HDBSCAN 1.0 minPts=58
k=1
Clustering
AGNES 1.0 method=single
metric=euclidean
k=4
Clustering
c-Means 1.0 k=2
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=8 Clustering
DIANA 1.0 metric=euclidean
k=3
Clustering
DBSCAN 1.0 eps=4.6477550614367695
MinPts=360
Clustering
Hierarchical Clustering 1.0 method=single
k=12
Clustering
fanny 1.0 k=5
membexp=2.0
Clustering
k-Means 1.0 k=8
nstart=10
Clustering
DensityCut 1.0 alpha=0.1976190476190476
K=60
Clustering
clusterONE 1.0 s=200
d=0.4
Clustering
Affinity Propagation 1.0 dampfact=0.9175
preference=0.0
maxits=2000
convits=200
Clustering
Markov Clustering 1.0 I=4.414114114114115 Clustering
Transitivity Clustering 1.0 T=10.537702917071353 Clustering
MCODE 0.909 v=0.9
cutoff=12.781326418951116
haircut=F
fluff=F
Clustering