非确定先验信息的贝叶斯网结构学习方法
비학정선험신식적패협사망결구학습방법
Structure Learning Method of Bayesian Network with Uncertain Prior Information
  • 万方数据
    计算机工程 계산궤공정
    COMPUTER ENGINEERING
    2010年 5期 165-167 ,共3页

    刘明辉%王磊%党林阁%石景岚

    류명휘%왕뢰%당림각%석경람

    贝叶斯网络%结构学习%专家知识%模拟退火 貝葉斯網絡%結構學習%專傢知識%模擬退火
    패협사망락%결구학습%전가지식%모의퇴화
    Bayesian network%structure learning%expert knowledge%simulated annealing
    针对非确定先验结构信息下的贝叶斯网络学习问题,提出一种非确定先验结构信息贝叶斯网络的结构学习方法.为更好地利用不确定性信息,对MDL测度进行改进,提出SMDL测度,使之能在学习过程中考虑先验信息的不确定性,使用模拟退火算法对问题进行求解.通过实验对算法的可行性和效率进行验证.
    침대비학정선험결구신식하적패협사망락학습문제,제출일충비학정선험결구신식패협사망락적결구학습방법.위경호지이용불학정성신식,대MDL측도진행개진,제출SMDL측도,사지능재학습과정중고필선험신식적불학정성,사용모의퇴화산법대문제진행구해.통과실험대산법적가행성화효솔진행험증.
    This paper presents a structure learning method of Bayesian network to solve the problem of structure learning with uncertain prior information.A description method of the uncertain prior information is given.An improved MDL score method named SMDL is proposed to fit the uncertain prior information in learning process.Simulated annealing method is used to solve the problem.This method is validated by experiments.
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