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=770
samples=20		 Clustering
Self Organizing Maps 0.0 x=788
y=735		 Clustering
Spectral Clustering 0.006 k=62 Clustering
clusterdp 0.0 k=16
dc=2.587697389143054		 Clustering
HDBSCAN 0.0 minPts=15
k=164		 Clustering
AGNES 0.0 method=single
metric=euclidean
k=62		 Clustering
c-Means 0.0 k=788
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=191 Clustering
DIANA 0.0 metric=euclidean
k=650		 Clustering
DBSCAN 0.0 eps=1.293848694571527
MinPts=683		 Clustering
Hierarchical Clustering 0.0 method=average
k=688		 Clustering
fanny 0.0 k=200
membexp=2.0		 Clustering
k-Means 0.0 k=528
nstart=10		 Clustering
DensityCut 0.0 alpha=9.765625E-4
K=10		 Clustering
clusterONE 0.783 s=27
d=0.7666666666666667		 Clustering
Affinity Propagation 0.002 dampfact=0.99
preference=0.0
maxits=5000
convits=425		 Clustering
Markov Clustering 0.783 I=3.1045045045045048 Clustering
Transitivity Clustering 0.0 T=38.349209055318234 Clustering
MCODE 0.001 v=0.8
cutoff=35.58083910071699
haircut=F
fluff=F		 Clustering