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 0.064 metric=euclidean
k=41
samples=20
Clustering
Self Organizing Maps 0.075 x=2
y=1
Clustering
Spectral Clustering 0.075 k=2 Clustering
clusterdp 0.13 k=2
dc=0.0
Clustering
HDBSCAN 0.13 minPts=32
k=2
Clustering
AGNES 0.103 method=single
metric=euclidean
k=2
Clustering
c-Means 0.091 k=13
m=5.0
Clustering
k-Medoids (PAM) 0.064 k=4 Clustering
DIANA 0.075 metric=euclidean
k=3
Clustering
DBSCAN 0.004 eps=14.686859132183113
MinPts=7
Clustering
Hierarchical Clustering 0.103 method=average
k=2
Clustering
fanny 0.09 k=28
membexp=7.626666666666667
Clustering
k-Means 0.075 k=3
nstart=10
Clustering
DensityCut 0.03 alpha=7.8125E-4
K=3
Clustering
clusterONE 0.07 s=18
d=0.16666666666666666
Clustering
Markov Clustering NaN I=1.2336336336336338 Clustering
Transitivity Clustering 0.13 T=2.793296531646438 Clustering
MCODE 0.046 v=0.4
cutoff=3.059762319204815
haircut=T
fluff=T
Clustering