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=83
samples=20		 Clustering
Self Organizing Maps 0.0 x=33
y=301		 Clustering
Spectral Clustering 0.0 k=86 Clustering
clusterdp 0.0 k=12
dc=28.28723779767516		 Clustering
HDBSCAN 0.0 minPts=6
k=53		 Clustering
AGNES 0.0 method=complete
metric=euclidean
k=232		 Clustering
c-Means 0.0 k=221
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=311 Clustering
DIANA 0.0 metric=euclidean
k=303		 Clustering
DBSCAN 0.0 eps=22.225686841030484
MinPts=260		 Clustering
Hierarchical Clustering 0.0 method=complete
k=212		 Clustering
fanny 0.0 k=98
membexp=1.1		 Clustering
k-Means 0.0 k=130
nstart=10		 Clustering
DensityCut 0.0 alpha=0.2777777777777778
K=7		 Clustering
clusterONE 0.669 s=208
d=0.36666666666666664		 Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=22.73081608741754
maxits=2000
convits=275		 Clustering
Markov Clustering 0.669 I=8.592392392392393 Clustering
Transitivity Clustering 0.0 T=27.880707353135428 Clustering
MCODE 0.006 v=0.2
cutoff=26.519285435320466
haircut=T
fluff=F		 Clustering