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=221
samples=20		 Clustering
Self Organizing Maps 0.0 x=11
y=180		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=24
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=1
k=285		 Clustering
AGNES 0.0 method=single
metric=euclidean
k=274		 Clustering
c-Means 0.0 k=284
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=281 Clustering
DIANA 0.0 metric=euclidean
k=109		 Clustering
DBSCAN 0.0 eps=0.9765301383526837
MinPts=280		 Clustering
Hierarchical Clustering 0.0 method=complete
k=174		 Clustering
fanny 0.0 k=119
membexp=1.1		 Clustering
k-Means 0.0 k=134
nstart=10		 Clustering
DensityCut 0.0 alpha=0.06914682539682541
K=2		 Clustering
clusterONE 1.0 s=100
d=0.36666666666666664		 Clustering
Affinity Propagation 0.0 dampfact=0.9175
preference=29.29590415058051
maxits=5000
convits=425		 Clustering
Markov Clustering 0.352 I=9.118018018018018 Clustering
Transitivity Clustering 0.0 T=28.94400139802098 Clustering