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 0.75 metric=euclidean
k=12
samples=20
Clustering
Self Organizing Maps 0.745 x=2
y=1
Clustering
Spectral Clustering 0.864 k=2 Clustering
clusterdp 0.795 k=3
dc=1.9530602767053673
Clustering
HDBSCAN 0.84 minPts=2
k=24
Clustering
AGNES 0.799 method=weighted
metric=euclidean
k=7
Clustering
c-Means 0.748 k=2
m=3.5
Clustering
k-Medoids (PAM) 0.75 k=2 Clustering
DIANA 0.745 metric=euclidean
k=3
Clustering
DBSCAN 0.946 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.763 method=average
k=2
Clustering
fanny 0.754 k=7
membexp=2.0
Clustering
k-Means 0.745 k=2
nstart=10
Clustering
DensityCut 0.87 alpha=0.3579365079365079
K=6
Clustering
clusterONE 0.715 s=1
d=0.9666666666666667
Clustering
Affinity Propagation 0.715 dampfact=0.845
preference=14.647952075290254
maxits=4250
convits=500
Clustering
Markov Clustering 0.742 I=9.331831831831831 Clustering
Transitivity Clustering 0.732 T=14.662614689980234 Clustering