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 1.0 metric=euclidean
k=9
samples=20
Clustering
Self Organizing Maps 0.99 x=2
y=1
Clustering
Spectral Clustering 0.932 k=4 Clustering
clusterdp 0.99 k=2
dc=0.0
Clustering
HDBSCAN 1.0 minPts=140
k=7
Clustering
AGNES 1.0 method=single
metric=euclidean
k=1
Clustering
c-Means 0.99 k=20
m=2.25
Clustering
k-Medoids (PAM) 0.547 k=3 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=0.0
MinPts=20
Clustering
Hierarchical Clustering 0.99 method=average
k=3
Clustering
fanny 1.0 k=8
membexp=1.1
Clustering
k-Means 0.932 k=2
nstart=10
Clustering
DensityCut 1.0 alpha=0.09523809523809523
K=10
Clustering
clusterONE 1.0 s=1
d=0.06666666666666667
Clustering
Markov Clustering 1.0 I=1.117817817817818 Clustering
Transitivity Clustering 1.0 T=0.01822828135870473 Clustering
MCODE 1.0 v=0.3
cutoff=7.587522115560845
haircut=T
fluff=T
Clustering