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=238
samples=20		 Clustering
Self Organizing Maps 0.0 x=10
y=133		 Clustering
Spectral Clustering 0.046 k=25 Clustering
clusterdp 0.0 k=10
dc=1.4104703215341545		 Clustering
HDBSCAN 0.0 minPts=131
k=226		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=119		 Clustering
c-Means 0.0 k=204
m=3.5		 Clustering
k-Medoids (PAM) 0.0 k=47 Clustering
DIANA 0.0 metric=euclidean
k=87		 Clustering
DBSCAN 0.0 eps=0.36567749076811407
MinPts=1		 Clustering
Hierarchical Clustering 0.0 method=average
k=228		 Clustering
fanny 0.0 k=50
membexp=2.0		 Clustering
k-Means 0.0 k=219
nstart=10		 Clustering
DensityCut 0.0 alpha=0.09761904761904762
K=15		 Clustering
clusterONE 0.739 s=108
d=1.0		 Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=1.1753919346117954
maxits=4250
convits=350		 Clustering
Markov Clustering 0.739 I=5.563363363363364 Clustering
Transitivity Clustering 0.0 T=1.4652199758791016 Clustering
MCODE 0.0 v=0.4
cutoff=1.2406914865346728
haircut=F
fluff=T		 Clustering