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=4
samples=20
Clustering
Self Organizing Maps 0.651 x=18
y=84
Clustering
Spectral Clustering 0.709 k=22 Clustering
clusterdp 1.0 k=3
dc=1.0970324723043423
Clustering
HDBSCAN 1.0 minPts=2
k=4
Clustering
AGNES 1.0 method=complete
metric=euclidean
k=4
Clustering
c-Means 1.0 k=4
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=4 Clustering
DIANA 0.857 metric=euclidean
k=3
Clustering
DBSCAN 1.0 eps=1.3582306799958523
MinPts=200
Clustering
Hierarchical Clustering 1.0 method=complete
k=3
Clustering
fanny 1.0 k=5
membexp=1.1
Clustering
k-Means 1.0 k=5
nstart=10
Clustering
DensityCut 1.0 alpha=0.9523809523809523
K=12
Clustering
clusterONE 0.415 s=1
d=0.1
Clustering
Affinity Propagation 0.657 dampfact=0.7725
preference=0.0
maxits=5000
convits=425
Clustering
Markov Clustering 0.415 I=1.1712712712712714 Clustering
Transitivity Clustering 0.961 T=0.9977300906414439 Clustering
MCODE 0.888 v=0
cutoff=0.7182950711516526
haircut=T
fluff=T
Clustering