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=188
samples=20
Clustering
Self Organizing Maps 1.0 x=160
y=200
Clustering
Spectral Clustering 0.996 k=59 Clustering
clusterdp 0.978 k=5
dc=4.895619710727704
Clustering
HDBSCAN 1.0 minPts=7
k=200
Clustering
AGNES 1.0 method=single
metric=euclidean
k=185
Clustering
c-Means 1.0 k=32
m=1.01
Clustering
k-Medoids (PAM) 1.0 k=194 Clustering
DIANA 1.0 metric=euclidean
k=184
Clustering
DBSCAN 1.0 eps=8.812115479309869
MinPts=1
Clustering
Hierarchical Clustering 1.0 method=average
k=188
Clustering
fanny 1.0 k=21
membexp=5.846666666666667
Clustering
k-Means 1.0 k=188
nstart=10
Clustering
DensityCut 0.917 alpha=0.0
K=2
Clustering
clusterONE 0.994 s=3
d=0.7
Clustering
Markov Clustering 0.0 I=3.6568568568568574 Clustering
Transitivity Clustering 1.0 T=7.203764739509235 Clustering
MCODE 0.948 v=0.1
cutoff=4.895619710727704
haircut=T
fluff=T
Clustering