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基于先验节点序学习贝叶斯网络结构的优化方法

朱明敏 刘三阳 汪春峰

朱明敏, 刘三阳, 汪春峰. 基于先验节点序学习贝叶斯网络结构的优化方法. 自动化学报, 2011, 37(12): 1514-1519. doi: 10.3724/SP.J.1004.2011.01514
引用本文: 朱明敏, 刘三阳, 汪春峰. 基于先验节点序学习贝叶斯网络结构的优化方法. 自动化学报, 2011, 37(12): 1514-1519. doi: 10.3724/SP.J.1004.2011.01514
ZHU Ming-Min, LIU San-Yang, WANG Chun-Feng. An Optimization Approach for Structural Learning Bayesian Networks Based on Prior Node Ordering. ACTA AUTOMATICA SINICA, 2011, 37(12): 1514-1519. doi: 10.3724/SP.J.1004.2011.01514
Citation: ZHU Ming-Min, LIU San-Yang, WANG Chun-Feng. An Optimization Approach for Structural Learning Bayesian Networks Based on Prior Node Ordering. ACTA AUTOMATICA SINICA, 2011, 37(12): 1514-1519. doi: 10.3724/SP.J.1004.2011.01514

基于先验节点序学习贝叶斯网络结构的优化方法

doi: 10.3724/SP.J.1004.2011.01514
详细信息
    通讯作者:

    朱明敏 博士研究生. 主要研究方向为优化算法及其在贝叶斯网络结构学习中的应用. E-mail: zhumingmin2009@yahoo.cn

An Optimization Approach for Structural Learning Bayesian Networks Based on Prior Node Ordering

  • 摘要: 针对小样本数据集下学习贝叶斯网络 (Bayesian networks, BN)结构的不足, 以及随着条件集的增大, 利用统计方法进行条件独立 (Conditional independence, CI) 测试不稳定等问题, 提出了一种基于先验节点序学习网络结构的优化方法. 新方法通过定义优化目标函数和可行域空间, 首次将贝叶斯网络结构学习问题转化为求解目标函数极值的数学规划问题, 并给出最优解的存在性及唯一性证明, 为贝叶斯网络的不断扩展研究提出了新的方案. 理论证明以及实验结果显示了新方法的正确性和有效性.
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出版历程
  • 收稿日期:  2011-04-15
  • 修回日期:  2011-06-29
  • 刊出日期:  2011-12-20

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