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=314
samples=20		 Clustering
Self Organizing Maps 0.0 x=788
y=604		 Clustering
Spectral Clustering 0.0 k=118 Clustering
clusterdp 0.0 k=14
dc=2.587697389143054		 Clustering
HDBSCAN 0.0 minPts=184
k=630		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=174		 Clustering
c-Means 0.0 k=327
m=5.0		 Clustering
k-Medoids (PAM) 0.0 k=687 Clustering
DIANA 0.0 metric=euclidean
k=701		 Clustering
DBSCAN 0.0 eps=0.0
MinPts=525		 Clustering
Hierarchical Clustering 0.0 method=average
k=766		 Clustering
fanny 0.0 k=146
membexp=2.0		 Clustering
k-Means 0.0 k=542
nstart=10		 Clustering
DensityCut 0.0 alpha=0.0
K=13		 Clustering
clusterONE 1.0 s=630
d=1.0		 Clustering
Affinity Propagation 0.0 dampfact=0.99
preference=38.815460837145814
maxits=5000
convits=500		 Clustering
Markov Clustering 1.0 I=2.507607607607608 Clustering
Transitivity Clustering 0.0 T=38.58233494623203 Clustering
MCODE 0.0 v=0.8
cutoff=35.58083910071699
haircut=T
fluff=F		 Clustering