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=74
samples=20		 Clustering
Self Organizing Maps 1.0 x=136
y=301		 Clustering
Spectral Clustering 1.0 k=32 Clustering
clusterdp 1.0 k=25
dc=9.092326434967017		 Clustering
HDBSCAN 1.0 minPts=4
k=89		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=114		 Clustering
c-Means 1.0 k=258
m=2.25		 Clustering
k-Medoids (PAM) 1.0 k=192 Clustering
DIANA 1.0 metric=euclidean
k=93		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=11		 Clustering
Hierarchical Clustering 1.0 method=average
k=227		 Clustering
fanny 1.0 k=104
membexp=2.0		 Clustering
k-Means 1.0 k=144
nstart=10		 Clustering
DensityCut 1.0 alpha=0.06696428571428571
K=3		 Clustering
clusterONE 0.0 s=104
d=0.4666666666666667		 Clustering
Affinity Propagation 1.0 dampfact=0.7
preference=22.73081608741754
maxits=3500
convits=350		 Clustering
Markov Clustering 0.0 I=6.534434434434434 Clustering
Transitivity Clustering 1.0 T=28.608821582161816 Clustering
MCODE 1.0 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=F		 Clustering