| 小数据集贝叶斯网络多父节点参数的修复 |
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| 引用本文： | 王双成,冷翠平,曹锋.小数据集贝叶斯网络多父节点参数的修复[J].计算机研究与发展,2009,46(5). |
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| 作者姓名： | 王双成 冷翠平 曹锋 |
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| 作者单位： | 1. 上海立信会计学院信息科学系,上海,201620;上海立信会计学院开放经济与贸易研究中心,上海,201620
2. 上海立信会计学院信息科学系,上海,201620 |
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| 基金项目： | 国家自然科学基金，上海市教委科研创新重点基金 |
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| 摘 要： | 具有已知结构的小数据集贝叶斯网络多父节点参数学习是一个重要而困难的研究课题,由于信息不充分,使得无法直接对多父节点参数进行有效的估计,如何修复这些参数便是问题的核心.针对问题提出了一种有效的小数据集多父节点参数修复方法,该方法首先使用Bootstrap抽样扩展小数据集,然后分别将Gibbs抽样与最大似然树和贝叶斯网络相结合,通过依次对扩展数据按一定比例的迭代修正来实现对多父节点参数的修复.实验结果表明,这种方法能够有效地使大部分多父节点参数得到修复.
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| 关 键 词： | 贝叶斯网络 小数据集 参数学习 Gibbs抽样 最大似然树 |
Revising the Parameters of Bayesian Network with Multi-Father Nodes from Small Data Set |
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| Wang Shuangcheng,Leng Cuiping,Cao Feng.Revising the Parameters of Bayesian Network with Multi-Father Nodes from Small Data Set[J].Journal of Computer Research and Development,2009,46(5). |
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| Authors: | Wang Shuangcheng Leng Cuiping Cao Feng |
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| Affiliation: | Department of Information Science;Shanghai Lixin University of Commerce;Shanghai 201620;Openting Economy & Trade Research Center;Shanghai 201620 |
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| Abstract: | Bayesian networks are graphical representations of dependency relationships between variables.They are intuitive representations of knowledge and are akin to human reasoning paradigms.They are powerful tools to deal with uncertainties,and have been extensively used to the representation and reasoning of uncertain knowledge.In the past decades,they have been successfully applied in medical diagnoses,software intelligence,finance risk analysis,DNA functional analysis,Web mining and so on;and have become a rap... |
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| Keywords: | Bayesian networks small data set parameter learning Gibbs sampling maximum likelihood tree |
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