Clusteval logo ClustEval clustering evaluation framework
Location: Data Sets » brown » 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
Spectral Clustering 1.0 k=217 Clustering
clusterdp 1.0 k=5
dc=247.86809842972212		 Clustering
AGNES 1.0 method=complete
metric=euclidean
k=170		 Clustering
c-Means 1.0 k=2
m=3.5		 Clustering
k-Medoids (PAM) 1.0 k=114 Clustering
DIANA 1.0 metric=euclidean
k=217		 Clustering
DBSCAN 1.0 eps=0.0
MinPts=1		 Clustering
Hierarchical Clustering 1.0 method=single
k=110		 Clustering
fanny 1.0 k=55
membexp=1.1		 Clustering
clusterONE 0.989 s=1
d=0.1		 Clustering
Affinity Propagation 0.996 dampfact=0.9175
preference=80.82655383577895
maxits=5000
convits=500		 Clustering
Markov Clustering 0.997 I=9.207107107107106 Clustering
Transitivity Clustering 1.0 T=323.3062153431158 Clustering
MCODE 0.995 v=0.3
cutoff=40.413276917889476
haircut=T
fluff=T		 Clustering