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基于预测能力的连续贝叶斯网络结构学习
引用本文:董立岩,苑森淼,刘光远,李永丽.基于预测能力的连续贝叶斯网络结构学习[J].计算机工程与应用,2007,43(9):23-24,48.
作者姓名:董立岩  苑森淼  刘光远  李永丽
作者单位:1. 吉林大学,计算机科学与技术学院,长春,130012
2. 吉林大学,通信工程学院,长春,130012
3. 东北师范大学,计算机学院,长春,130024
摘    要:通过对连续随机变量之间预测能力及其计算方法的讨论,提出基于预测能力的连续贝叶斯网络结构学习方法。该方法包括两个步骤,每个步骤都伴随环路检验。首先建立初始贝叶斯网络结构,其次调整初始贝叶斯网络结构,包括增加丢失的弧、删除多余的弧及调整弧的方向,并使用模拟数据进行了对比实验,结果表明该方法非常有致。

关 键 词:连续贝叶斯网络  预测能力  最小切割集
文章编号:1002-8331(2007)09-0023-02
修稿时间:2007-01

Learning of continuous Bayesian networks structure from data set based on forecasting ability
DONG Li-yan,YUAN Sen-miao,LIU Guang-yuan,LI Yong-li.Learning of continuous Bayesian networks structure from data set based on forecasting ability[J].Computer Engineering and Applications,2007,43(9):23-24,48.
Authors:DONG Li-yan  YUAN Sen-miao  LIU Guang-yuan  LI Yong-li
Affiliation:1.College of Computer Science and Technology,Jilin University,Changchun 130012,China; 2.College of Communication Engineering,Jilin University,Changchun 130012,China ;3.College of Computer,Northeast Normal University,Changchun 130024,China
Abstract:In this paper,the definition of forecasting ability and its calculational method are presented between two continuous variables.A method of learning continuous Bayesian networks structure from data set based on forecasting ability is developed. This method is made up of two parts.Each part is combined with checking a cyclic route in a directed graph.Firstly,an elementary Bayesian network structure is set up.Secondly,this elementary Bayesian network structure is regulated,including to increase the losed arcs,to delete superfluous ares and to regulate direction of arcs.The experiment is made by using simulant data and the experimental results are shown by the means of contrasting.
Keywords:continuous Bayesian network  forecasting ability  minimum d-separating set
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