标题：Naive Bayes classifiers learned from incomplete data
作者：Chen, Jingnian ;Huang, Houkuan ;Tian, Fengzhan ;Qiao, Zhufeng
作者机构： School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China; Dept. of Mathematics, Shandong University of F 更多
来源：Jisuanji Gongcheng/Computer Engineering
摘要：Bayes networks, as directed acyclic graphs of causal structure of attributes, have become the efficient method for processing incomplete data. However, most Bayesian network classifiers are learned from complete data and the world is rarely fully observable and data is often incomplete. So constructing Bayesian network classifiers from incomplete data is an important and challenging problem. An efficient method for constructing Bayesian network classifiers from incomplete data based on BC method and EM algorithm is presented. Experimental results show its validity.