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基于最大主子图分解的贝叶斯网络等价类学习算法

, PP. 1499-1504

Keywords: 贝叶斯网络,最大主子图分解,条件独立测,结构学习,马尔科夫等价类

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Abstract:

针对基于约束方法学习贝叶斯网络(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(CI)测试不稳定等问题,提出一种基于最大主子图分解(MPD)的BN等价类学习算法.该算法首先通过MPD分解技术对BN的道德图进行分解;然后利用0阶和1阶CI测试识别部分子图中的V结构,对于初步未定的V结构利用局部评分搜索确定,从而避免了冗余检验,有效地减小了条件集的维数,并且提高了算法的效率;最后,理论证明以及实验结果表明了所提出算法的有效性和合理性.

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