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=172
samples=20		 Clustering
Self Organizing Maps 0.0 x=33
y=1		 Clustering
Spectral Clustering 0.0 k=60 Clustering
clusterdp 0.0 k=11
dc=28.28723779767516		 Clustering
HDBSCAN 0.0 minPts=11
k=89		 Clustering
AGNES 0.0 method=ward
metric=euclidean
k=88		 Clustering
c-Means 0.0 k=249
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=306 Clustering
DIANA 0.0 metric=euclidean
k=159		 Clustering
DBSCAN 0.0 eps=14.14361889883758
MinPts=280		 Clustering
Hierarchical Clustering 0.0 method=complete
k=102		 Clustering
fanny 0.0 k=62
membexp=2.0		 Clustering
k-Means 0.0 k=82
nstart=10		 Clustering
DensityCut 0.0 alpha=0.06430697278911565
K=4		 Clustering
clusterONE 1.0 s=280
d=0.2		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=22.73081608741754
maxits=4250
convits=200		 Clustering
Markov Clustering 1.0 I=6.837337337337337 Clustering
Transitivity Clustering 0.0 T=28.032397817515925 Clustering
MCODE 0.0 v=0.2
cutoff=26.519285435320466
haircut=F
fluff=T		 Clustering