Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » synthetic_spirals » 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=160
samples=20		 Clustering
Self Organizing Maps 0.0 x=26
y=191		 Clustering
Spectral Clustering 0.0 k=19 Clustering
clusterdp 0.0 k=7
dc=0.552		 Clustering
HDBSCAN 0.0 minPts=190
k=250		 Clustering
AGNES 0.0 method=complete
metric=euclidean
k=164		 Clustering
c-Means 0.0 k=209
m=5.0		 Clustering
k-Medoids (PAM) 0.0 k=175 Clustering
DIANA 0.0 metric=euclidean
k=104		 Clustering
DBSCAN 0.0 eps=0.3312
MinPts=75		 Clustering
Hierarchical Clustering 0.0 method=complete
k=155		 Clustering
fanny 0.0 k=113
membexp=5.0		 Clustering
k-Means 0.0 k=244
nstart=10		 Clustering
DensityCut 0.0 alpha=0.06505102040816325
K=8		 Clustering
clusterONE 1.0 s=183
d=0.4666666666666667		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=3.3120000000000003
maxits=3500
convits=275		 Clustering
Markov Clustering 0.5 I=8.85965965965966 Clustering
Transitivity Clustering 0.0 T=2.9970450450450454 Clustering
MCODE 0.001 v=0.6
cutoff=3.036
haircut=T
fluff=T		 Clustering