On the study of BKYY cluster number selection criterion for small sample data set with bootstrap technique
Ping Guo, Lei Xu · 2003
The Bayesian-Kullback ying-yang (BKYY) learning theory and system has been proposed by Xu (1995, 1997), and one special case of ying-yang system can provide the model selection criteria for selecting the number of clusters in the clustering analysis. In this paper, we present an experimental study of this cluster number selection criterion in a small number sample set case. The results show that the criterion performed reasonable well when mixture parameters were estimated by incorporating a bootstrap technique with the EM algorithm.