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=173
samples=20		 Clustering
Self Organizing Maps 0.0 x=131
y=10		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=22
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=270
k=300		 Clustering
AGNES 0.0 method=weighted
metric=euclidean
k=289		 Clustering
c-Means 0.0 k=67
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=222 Clustering
DIANA 0.0 metric=euclidean
k=162		 Clustering
DBSCAN 0.0 eps=12.694891798584885
MinPts=220		 Clustering
Hierarchical Clustering 0.0 method=complete
k=286		 Clustering
fanny 0.0 k=144
membexp=1.1		 Clustering
k-Means 0.0 k=224
nstart=10		 Clustering
DensityCut 0.0 alpha=0.06914682539682541
K=2		 Clustering
clusterONE 1.0 s=140
d=0.03333333333333333		 Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=2000
convits=500		 Clustering
Markov Clustering 0.352 I=9.091291291291292 Clustering
Transitivity Clustering 0.0 T=28.856025709881102 Clustering