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=93
samples=20		 Clustering
Self Organizing Maps 0.0 x=71
y=180		 Clustering
Spectral Clustering 0.0 k=8 Clustering
clusterdp 0.0 k=23
dc=0.9765301383526837		 Clustering
HDBSCAN 0.0 minPts=6
k=183		 Clustering
AGNES 0.0 method=flexible
metric=euclidean
k=88		 Clustering
c-Means 0.0 k=53
m=1.01		 Clustering
k-Medoids (PAM) 0.0 k=121 Clustering
DIANA 0.0 metric=euclidean
k=209		 Clustering
DBSCAN 0.0 eps=13.671421936937572
MinPts=230		 Clustering
Hierarchical Clustering 0.0 method=complete
k=265		 Clustering
fanny 0.0 k=131
membexp=1.1		 Clustering
k-Means 0.0 k=296
nstart=10		 Clustering
DensityCut 0.0 alpha=0.1040107709750567
K=2		 Clustering
clusterONE 1.0 s=260
d=0.7		 Clustering
Affinity Propagation 0.0 dampfact=0.7725
preference=21.97192811293538
maxits=5000
convits=425		 Clustering
Markov Clustering 0.352 I=9.26946946946947 Clustering
Transitivity Clustering 0.0 T=28.005594057862247 Clustering