Comparison on based Clustering Bayesian YING-YANG Theory Number Selection Criterion with Information Theoretical Criteria
Peng Wei Guo, Li Xu · 1998
Recently, a criterion based on the Bayesian Ying Yang Learning Theory and System has been pro- posed by Xu(& 9,101 for selecting the number of clusters in the clustering analysis and the number of Guassians in a finite mixture model. In this paper we compare the performance of this criterion with other existing cluster number selection criteria such as AIC, CAIC etc.