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=66
samples=20		 Clustering
Self Organizing Maps 0.0 x=167
y=1		 Clustering
Spectral Clustering 0.0 k=45 Clustering
clusterdp 0.0 k=9
dc=3.2016		 Clustering
HDBSCAN 0.0 minPts=214
k=250		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=237		 Clustering
c-Means 0.0 k=89
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=248 Clustering
DIANA 0.0 metric=euclidean
k=78		 Clustering
DBSCAN 0.0 eps=1.5456
MinPts=233		 Clustering
Hierarchical Clustering 0.0 method=average
k=100		 Clustering
fanny 0.0 k=118
membexp=5.0		 Clustering
k-Means 0.0 k=247
nstart=10		 Clustering
DensityCut 0.0 alpha=0.06505102040816325
K=8		 Clustering
clusterONE 1.0 s=34
d=0.8333333333333334		 Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=3.3120000000000003
maxits=2000
convits=425		 Clustering
Markov Clustering 0.5 I=9.74164164164164 Clustering
Transitivity Clustering 0.0 T=2.9473153153153158 Clustering
MCODE 0.001 v=0.6
cutoff=3.036
haircut=T
fluff=T		 Clustering