计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (3): 195-197.

• 数据库与信息处理 • 上一篇    下一篇

基于预测关系的贝叶斯网络学习算法

张剑飞1,王双成2   

  1. 1.齐齐哈尔大学 计算机与控制工程学院,黑龙江 齐齐哈尔 161006
    2.上海立信会计学院 信息科学系,上海 201600
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-01-21 发布日期:2008-01-21
  • 通讯作者: 张剑飞

Bayesian networks learning scheme based on prediction relationship

ZHANG Jian-fei1,WANG Shuang-cheng2   

  1. 1.College of Computer and Control Engineering,Qiqihr University,Qiqihr,Heilongjiang 161006,China
    2.Department of Information Science,Shanghai Lixin University of Commerce,Shanghai 201600,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-01-21 Published:2008-01-21
  • Contact: ZHANG Jian-fei

摘要: 在介绍有代表性的贝叶斯网络结构学习算法基础上,给出了变量之间预测能力的概念及估计方法,并证明了预测能力就是预测正确率,在此基础上建立了基于变量之间预测关系的贝叶斯网络结构学习方法,并使用模拟数据进行了对比实验,实验结果显示该算法能够有效地进行贝叶斯网络结构学习。

关键词: 贝叶斯网络, 结构学习, 预测能力

Abstract: In the paper,representative Bayesian networks learning methods are analyzed;the concept and estimating methods of the prediction ability are given.At the same time,it is proven that the prediction ability is the accurate of the prediction.The method of Bayesian networks structure learning based on prediction ability is developed.The experiment is made by simulation;experimental results show that Bayesian networks structure can be learned by this scheme effectively.

Key words: Bayesian networks, structure learning, prediction ability