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 0.0 metric=euclidean
k=197
samples=20		 Clustering
Self Organizing Maps 0.0 x=208
y=166		 Clustering
Spectral Clustering 0.0 k=21 Clustering
clusterdp 0.0 k=15
dc=27.276979304901047		 Clustering
HDBSCAN 0.0 minPts=75
k=312		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=39		 Clustering
c-Means 0.0 k=127
m=3.5		 Clustering
k-Medoids (PAM) 0.0 k=151 Clustering
DIANA 0.0 metric=euclidean
k=193		 Clustering
DBSCAN 0.0 eps=21.21542834825637
MinPts=260		 Clustering
Hierarchical Clustering 0.0 method=average
k=252		 Clustering
fanny 0.0 k=117
membexp=2.0		 Clustering
k-Means 0.0 k=221
nstart=10		 Clustering
DensityCut 0.0 alpha=0.0547406462585034
K=8		 Clustering
clusterONE 1.0 s=208
d=0.7666666666666667		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=15.153877391611694
maxits=2000
convits=500		 Clustering
Markov Clustering 1.0 I=2.7926926926926927 Clustering
Transitivity Clustering 0.0 T=27.516650238622233 Clustering
MCODE 0.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=F		 Clustering