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=256
samples=20		 Clustering
Self Organizing Maps 0.0 x=270
y=200		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=23
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=29
k=257		 Clustering
AGNES 0.0 method=average
metric=euclidean
k=278		 Clustering
c-Means 0.0 k=269
m=5.0		 Clustering
k-Medoids (PAM) 0.0 k=153 Clustering
DIANA 0.0 metric=euclidean
k=245		 Clustering
DBSCAN 0.0 eps=13.671421936937572
MinPts=230		 Clustering
Hierarchical Clustering 0.0 method=single
k=35		 Clustering
fanny 0.0 k=133
membexp=2.0		 Clustering
k-Means 0.0 k=143
nstart=10		 Clustering
DensityCut 0.0 alpha=0.12144274376417233
K=2		 Clustering
clusterONE 1.0 s=190
d=0.2		 Clustering
Affinity Propagation 0.0 dampfact=0.7
preference=29.29590415058051
maxits=4250
convits=275		 Clustering
Markov Clustering 0.352 I=9.483283283283283 Clustering
Transitivity Clustering 0.0 T=28.298846351661854 Clustering