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=267
samples=20		 Clustering
Self Organizing Maps 0.0 x=300
y=240		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=23
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=28
k=53		 Clustering
AGNES 0.0 method=average
metric=euclidean
k=43		 Clustering
c-Means 0.0 k=164
m=2.25		 Clustering
k-Medoids (PAM) 0.0 k=208 Clustering
DIANA 0.0 metric=euclidean
k=294		 Clustering
DBSCAN 0.0 eps=13.671421936937572
MinPts=230		 Clustering
Hierarchical Clustering 0.0 method=complete
k=153		 Clustering
fanny 0.0 k=99
membexp=2.0		 Clustering
k-Means 0.0 k=238
nstart=10		 Clustering
DensityCut 0.005 alpha=0.08657879818594105
K=2		 Clustering
clusterONE 0.667 s=180
d=0.6		 Clustering
Affinity Propagation 0.0 dampfact=0.845
preference=29.29590415058051
maxits=4250
convits=200		 Clustering
Markov Clustering 0.471 I=9.75055055055055 Clustering
Transitivity Clustering 0.0 T=29.178603233060667 Clustering