Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » gionis_aggregation » 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=286
samples=20		 Clustering
Self Organizing Maps 0.0 x=788
y=735		 Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=7
dc=2.587697389143054		 Clustering
HDBSCAN 0.0 minPts=394
k=761		 Clustering
AGNES 0.0 method=single
metric=euclidean
k=113		 Clustering
c-Means 0.0 k=788
m=3.5		 Clustering
k-Medoids (PAM) 0.0 k=759 Clustering
DIANA 0.0 metric=euclidean
k=500		 Clustering
DBSCAN 0.0 eps=0.0
MinPts=1		 Clustering
Hierarchical Clustering 0.0 method=average
k=442		 Clustering
fanny 0.0 k=122
membexp=5.0		 Clustering
k-Means 0.0 k=775
nstart=10		 Clustering
DensityCut 0.0 alpha=3.255208333333333E-4
K=6		 Clustering
clusterONE 1.0 s=735
d=0.1		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=38.815460837145814
maxits=2000
convits=275		 Clustering
Markov Clustering 1.0 I=6.463163163163164 Clustering
Transitivity Clustering 0.0 T=34.81346637645911 Clustering
MCODE 0.0 v=0.9
cutoff=35.58083910071699
haircut=F
fluff=F		 Clustering