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=245
samples=20		 Clustering
Self Organizing Maps 0.0 x=250
y=250		 Clustering
Spectral Clustering 0.0 k=9 Clustering
clusterdp 0.0 k=8
dc=3.2016		 Clustering
HDBSCAN 0.0 minPts=1
k=29		 Clustering
AGNES 0.0 method=complete
metric=euclidean
k=189		 Clustering
c-Means 0.0 k=229
m=1.5		 Clustering
k-Medoids (PAM) 0.0 k=143 Clustering
DIANA 0.0 metric=euclidean
k=150		 Clustering
DBSCAN 0.0 eps=3.2016
MinPts=200		 Clustering
Hierarchical Clustering 0.0 method=average
k=176		 Clustering
fanny 0.0 k=102
membexp=2.0		 Clustering
k-Means 0.0 k=68
nstart=10		 Clustering
DensityCut 0.0 alpha=0.035713996206011074
K=4		 Clustering
clusterONE 1.0 s=142
d=1.0		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=3.3120000000000003
maxits=2750
convits=425		 Clustering
Markov Clustering 0.5 I=9.714914914914916 Clustering
Transitivity Clustering 0.0 T=3.0202522522522526 Clustering
MCODE 0.001 v=0.6
cutoff=3.036
haircut=F
fluff=T		 Clustering