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 0.869 metric=euclidean
k=5
samples=20
Clustering
Self Organizing Maps 0.544 x=2
y=27
Clustering
Spectral Clustering 0.943 k=9 Clustering
clusterdp 1.0 k=8
dc=2.587697389143054
Clustering
HDBSCAN 0.937 minPts=8
k=95
Clustering
AGNES 1.0 method=flexible
metric=euclidean
k=4
Clustering
c-Means 0.893 k=6
m=1.5
Clustering
k-Medoids (PAM) 0.858 k=6 Clustering
DIANA 0.841 metric=euclidean
k=6
Clustering
DBSCAN 0.864 eps=16.820033029429855
MinPts=683
Clustering
Hierarchical Clustering 0.967 method=single
k=6
Clustering
fanny 0.892 k=4
membexp=5.0
Clustering
k-Means 0.893 k=6
nstart=10
Clustering
DensityCut 1.0 alpha=0.00234375
K=13
Clustering
clusterONE 0.345 s=27
d=0.8333333333333334
Clustering
Affinity Propagation 0.485 dampfact=0.9175
preference=0.0
maxits=3500
convits=275
Clustering
Markov Clustering 0.345 I=1.6612612612612614 Clustering
Transitivity Clustering 0.975 T=30.73376328546781 Clustering
MCODE 0.864 v=0.4
cutoff=30.728906496073773
haircut=F
fluff=F
Clustering