Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » chang_spiral » Best Parameters
Navigation:
027Hints:

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 0.496 x=2
y=1		 Clustering
Spectral Clustering 0.854 k=3 Clustering
clusterdp 1.0 k=4
dc=27.276979304901047		 Clustering
HDBSCAN 1.0 minPts=1
k=15		 Clustering
AGNES 1.0 method=average
metric=euclidean
k=1		 Clustering
c-Means 0.496 k=2
m=1.01		 Clustering
k-Medoids (PAM) 0.5 k=13 Clustering
DIANA 1.0 metric=euclidean
k=1		 Clustering
DBSCAN 1.0 eps=22.225686841030484
MinPts=291		 Clustering
Hierarchical Clustering 1.0 method=complete
k=3		 Clustering
fanny 1.0 k=7
membexp=2.0		 Clustering
k-Means 0.496 k=2
nstart=10		 Clustering
DensityCut 1.0 alpha=0.03968253968253968
K=25		 Clustering
clusterONE 1.0 s=177
d=0.8		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=0.0
maxits=3500
convits=275		 Clustering
Markov Clustering 1.0 I=5.233733733733733 Clustering
Transitivity Clustering 1.0 T=10.04190874198893 Clustering
MCODE 0.496 v=0.7
cutoff=17.679523623546974
haircut=T
fluff=F		 Clustering