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 0.834 metric=euclidean
k=4
samples=20
Clustering
Self Organizing Maps 0.831 x=3
y=29
Clustering
Spectral Clustering 0.716 k=26 Clustering
clusterdp 0.923 k=5
dc=0.020339198944763118
Clustering
HDBSCAN 0.713 minPts=2
k=8
Clustering
AGNES 0.896 method=average
metric=euclidean
k=4
Clustering
c-Means 0.921 k=3
m=5.0
Clustering
k-Medoids (PAM) 0.9 k=4 Clustering
DIANA 0.858 metric=euclidean
k=4
Clustering
DBSCAN 0.933 eps=0.5491583715086041
MinPts=5
Clustering
Hierarchical Clustering 0.933 method=average
k=4
Clustering
fanny 0.921 k=3
membexp=1.1
Clustering
k-Means 0.921 k=3
nstart=10
Clustering
DensityCut 0.894 alpha=0.7558035714285714
K=2
Clustering
clusterONE 0.847 s=10
d=0.8333333333333334
Clustering
Affinity Propagation 0.948 dampfact=0.7
preference=0.0
maxits=2750
convits=425
Clustering
Markov Clustering 0.783 I=9.93763763763764 Clustering
Transitivity Clustering 0.933 T=0.26324909144723435 Clustering