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=3
samples=20
Clustering
Self Organizing Maps 0.931 x=2
y=1
Clustering
Spectral Clustering 1.0 k=14 Clustering
clusterdp 1.0 k=2
dc=1.1492721138426443
Clustering
HDBSCAN 1.0 minPts=9
k=3
Clustering
AGNES 1.0 method=single
metric=euclidean
k=2
Clustering
c-Means 1.0 k=3
m=1.5
Clustering
k-Medoids (PAM) 1.0 k=4 Clustering
DIANA 1.0 metric=euclidean
k=1
Clustering
DBSCAN 1.0 eps=0.20895856615320804
MinPts=108
Clustering
Hierarchical Clustering 1.0 method=single
k=3
Clustering
fanny 1.0 k=14
membexp=1.1
Clustering
k-Means 1.0 k=3
nstart=10
Clustering
DensityCut 1.0 alpha=0.04761159987676711
K=11
Clustering
clusterONE 1.0 s=84
d=0.3333333333333333
Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.3917973115372651
maxits=5000
convits=500
Clustering
Markov Clustering 1.0 I=6.1602602602602605 Clustering
Transitivity Clustering 1.0 T=0.580440461536689 Clustering
MCODE 0.852 v=0.9
cutoff=0.5223964153830202
haircut=F
fluff=F
Clustering