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=0.4179171323064161
Clustering
HDBSCAN 1.0 minPts=8
k=4
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=4
Clustering
c-Means 1.0 k=3
m=5.0
Clustering
k-Medoids (PAM) 1.0 k=4 Clustering
DIANA 0.857 metric=euclidean
k=3
Clustering
DBSCAN 1.0 eps=1.4104703215341545
MinPts=200
Clustering
Hierarchical Clustering 1.0 method=average
k=5
Clustering
fanny 1.0 k=4
membexp=1.1
Clustering
k-Means 1.0 k=5
nstart=10
Clustering
DensityCut 1.0 alpha=0.15873015873015872
K=10
Clustering
clusterONE 0.415 s=225
d=0.13333333333333333
Clustering
Affinity Propagation 0.657 dampfact=0.99
preference=0.0
maxits=4250
convits=350
Clustering
Markov Clustering 0.415 I=9.59019019019019 Clustering
Transitivity Clustering 0.961 T=0.9930238166289842 Clustering
MCODE 0.888 v=0
cutoff=0.7182950711516526
haircut=F
fluff=F
Clustering