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 0.0 metric=euclidean
k=682
samples=20
Clustering
Self Organizing Maps 0.0 x=788
y=735
Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=17
dc=2.587697389143054
Clustering
HDBSCAN 0.0 minPts=338
k=675
Clustering
AGNES 0.0 method=average
metric=euclidean
k=442
Clustering
c-Means 0.0 k=84
m=2.25
Clustering
k-Medoids (PAM) 0.0 k=787 Clustering
DIANA 0.0 metric=euclidean
k=400
Clustering
DBSCAN 0.0 eps=0.0
MinPts=1
Clustering
Hierarchical Clustering 0.0 method=single
k=650
Clustering
fanny 0.0 k=96
membexp=2.0
Clustering
k-Means 0.0 k=213
nstart=10
Clustering
DensityCut 0.0 alpha=0.00234375
K=10
Clustering
clusterONE 1.0 s=683
d=0.7666666666666667
Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=38.815460837145814
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=9.91981981981982 Clustering
Transitivity Clustering 0.0 T=38.27150042501364 Clustering
MCODE 0.0 v=0.7
cutoff=35.58083910071699
haircut=T
fluff=F
Clustering