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A Simple Method for Identifying Compelled Edges in DAGs

机译:识别DAG中强制边缘的简单方法

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摘要

Identifying compelled edges is important in learning the structure (i.e., the DAG) of a Bayesian network. A graphical method (Chickering 1995) was proposed to solve this problem. In this paper, we show that a joint probability distribution defined by a Bayesian network can be uniquely characterized by its intrinsic factorization. Based on such an algebraic characterization, we suggest a simple algorithm to identify the compelled edges of a Bayesian network structure.
机译:识别强制边缘对于学习贝叶斯网络的结构(即DAG)很重要。提出了一种图形方法(Chickering 1995)来解决这个问题。在本文中,我们证明了由贝叶斯网络定义的联合概率分布可以通过其内在因式分解来唯一表征。基于这种代数特征,我们建议一种简单的算法来识别贝叶斯网络结构的强迫边缘。

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