Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » chang_pathbased » 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=108
samples=20		 Clustering
Self Organizing Maps 0.0 x=270
y=150		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=21
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=12
k=153		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=165		 Clustering
c-Means 0.0 k=164
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=236 Clustering
DIANA 0.0 metric=euclidean
k=246		 Clustering
DBSCAN 0.0 eps=8.788771245174154
MinPts=210		 Clustering
Hierarchical Clustering 0.0 method=average
k=89		 Clustering
fanny 0.0 k=99
membexp=5.0		 Clustering
k-Means 0.0 k=188
nstart=10		 Clustering
DensityCut 0.005 alpha=0.06914682539682541
K=2		 Clustering
clusterONE 0.667 s=140
d=0.1		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=29.29590415058051
maxits=2000
convits=200		 Clustering
Markov Clustering 0.471 I=9.412012012012012 Clustering
Transitivity Clustering 0.0 T=28.914676168641023 Clustering