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 0.714 metric=euclidean
k=7
samples=20
Clustering
Self Organizing Maps 0.652 x=2
y=1
Clustering
Spectral Clustering 0.867 k=2 Clustering
clusterdp 0.735 k=4
dc=4.882650691763418
Clustering
HDBSCAN 0.807 minPts=5
k=7
Clustering
AGNES 0.807 method=weighted
metric=euclidean
k=7
Clustering
c-Means 0.707 k=6
m=2.25
Clustering
k-Medoids (PAM) 0.691 k=3 Clustering
DIANA 0.728 metric=euclidean
k=1
Clustering
DBSCAN 0.947 eps=21.48366304375904
MinPts=270
Clustering
Hierarchical Clustering 0.736 method=single
k=11
Clustering
fanny 0.711 k=2
membexp=5.0
Clustering
k-Means 0.696 k=3
nstart=10
Clustering
DensityCut 0.76 alpha=0.3579365079365079
K=6
Clustering
clusterONE 0.501 s=1
d=0.9666666666666667
Clustering
Affinity Propagation 0.501 dampfact=0.845
preference=14.647952075290254
maxits=4250
convits=500
Clustering
Markov Clustering 0.65 I=9.331831831831831 Clustering
Transitivity Clustering 0.73 T=21.642019282410825 Clustering