Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » synthetic_cuboid » 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=59
samples=20		 Clustering
Self Organizing Maps 0.0 x=26
y=92		 Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=22
dc=0.2611982076915101		 Clustering
HDBSCAN 0.0 minPts=1
k=131		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=54		 Clustering
c-Means 0.0 k=38
m=3.5		 Clustering
k-Medoids (PAM) 0.0 k=113 Clustering
DIANA 0.0 metric=euclidean
k=204		 Clustering
DBSCAN 0.0 eps=1.3582306799958523
MinPts=200		 Clustering
Hierarchical Clustering 0.0 method=complete
k=116		 Clustering
fanny 0.0 k=42
membexp=5.0		 Clustering
k-Means 0.0 k=88
nstart=10		 Clustering
DensityCut 0.0 alpha=0.012202380952380952
K=9		 Clustering
clusterONE 0.739 s=17
d=0.5		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=0.0
maxits=2000
convits=425		 Clustering
Markov Clustering 0.739 I=8.583483483483484 Clustering
Transitivity Clustering 0.0 T=1.4793387979164805 Clustering
MCODE 0.0 v=0.1
cutoff=1.1753919346117954
haircut=T
fluff=F		 Clustering