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 0.758 metric=euclidean
k=41
samples=20
Clustering
Self Organizing Maps 0.961 x=2
y=1
Clustering
Spectral Clustering 0.942 k=2 Clustering
clusterdp 0.716 k=25
dc=10.77036336360095
Clustering
HDBSCAN 0.512 minPts=73
k=113
Clustering
AGNES 0.844 method=flexible
metric=euclidean
k=2
Clustering
c-Means 0.956 k=2
m=2.25
Clustering
k-Medoids (PAM) 0.758 k=4 Clustering
DIANA 0.942 metric=euclidean
k=3
Clustering
DBSCAN 0.503 eps=14.686859132183113
MinPts=7
Clustering
Hierarchical Clustering 0.82 method=average
k=12
Clustering
fanny 0.951 k=2
membexp=1.99
Clustering
k-Means 0.951 k=3
nstart=10
Clustering
DensityCut 0.651 alpha=7.8125E-4
K=3
Clustering
clusterONE 0.861 s=18
d=0.16666666666666666
Clustering
Markov Clustering 0.497 I=1.2336336336336338 Clustering
Transitivity Clustering 0.748 T=4.572185375484433 Clustering
MCODE 0.622 v=0.9
cutoff=4.895619710727704
haircut=T
fluff=F
Clustering