A hybrid approach to learn Bayesian networks using evolutionary programming

M. Wong, Shing Yan Lee, K. Leung
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引用次数: 4

Abstract

A novel hybrid framework is reported that improves upon our previous work, MDLEP, which uses evolutionary programming to solve the difficult Bayesian network learning problem. A new merge operator is also introduced that further enhances the efficiency. As experimental results suggest, our hybrid approach performs significantly better than MDLEP.
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使用进化规划学习贝叶斯网络的混合方法
报告了一种新的混合框架,改进了我们以前的工作,MDLEP,它使用进化编程来解决困难的贝叶斯网络学习问题。引入了一种新的合并算子,进一步提高了合并效率。实验结果表明,我们的混合方法的性能明显优于MDLEP。
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