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=1
samples=20
Clustering
Self Organizing Maps 0.979 x=2
y=27
Clustering
Spectral Clustering 1.0 k=4 Clustering
clusterdp 1.0 k=4
dc=32.34621736428818
Clustering
HDBSCAN 1.0 minPts=788
k=1
Clustering
AGNES 1.0 method=complete
metric=euclidean
k=6
Clustering
c-Means 0.993 k=3
m=1.01
Clustering
k-Medoids (PAM) 0.995 k=2 Clustering
DIANA 1.0 metric=euclidean
k=2
Clustering
DBSCAN 1.0 eps=3.881546083714581
MinPts=551
Clustering
Hierarchical Clustering 1.0 method=average
k=9
Clustering
fanny 1.0 k=2
membexp=5.0
Clustering
k-Means 0.993 k=3
nstart=10
Clustering
DensityCut 1.0 alpha=0.06666666666666667
K=16
Clustering
clusterONE 1.0 s=420
d=0.03333333333333333
Clustering
Affinity Propagation 1.0 dampfact=0.7725
preference=0.0
maxits=2750
convits=500
Clustering
Markov Clustering 1.0 I=10.0 Clustering
Transitivity Clustering 1.0 T=2.2924045939855886 Clustering
MCODE 0.818 v=0.0
cutoff=35.58083910071699
haircut=F
fluff=F
Clustering