贝叶斯网的学习与应用研究综述  

A survey for learning and application research of Bayesian Networks

作　　者：李甦[1] 陈新亿[1] 李娟[1] 李斯娜[1] 

机构地区：[1]云南大学信息学院,云南昆明650091

出　　处：《云南大学学报（自然科学版）》2009年第S1期218-222,226,共6页Journal of Yunnan University(Natural Sciences Edition)

基　　金：云南省自然科学基金资助项目(2008CD085)

摘　　要：贝叶斯网的学习就是确定贝叶斯网的网络结构和条件概率表.本文从贝叶斯定理出发,首先介绍了贝叶斯网及贝叶斯网的学习;接着介绍了一些常用的贝叶斯网的学习算法,并对其进行了简要分析;最后介绍了贝叶斯网的应用,对贝叶斯网的学习的发展趋势作了展望.The learning of Bayesian Networks(BN) is to determine its network structure and conditional probability table. In this paper,starting from the Bayes theorem,we introduced the BN and the learning of BN at first.Then we introduced and briefly analyzed some commonly used learning algorithms of BN.At last,we introduced applications of BN and made some outlooks for the development trends of BN's learning.

关 键 词：贝叶斯网 参数学习 结构学习 评分函数 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]