ExpertBayes: Automatically refining manually built Bayesian networks.

Ezilda Almeida, Pedro Ferreira, Tiago Vinhoza, Inês Dutra, Jingwei Li, Yirong Wu, Elizabeth Burnside
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引用次数: 8

Abstract

Bayesian network structures are usually built using only the data and starting from an empty network or from a naïve Bayes structure. Very often, in some domains, like medicine, a prior structure knowledge is already known. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and show that minor perturbations to this original network can yield better classifiers with a very small computational cost, while maintaining most of the intended meaning of the original model.

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ExpertBayes:自动精炼人工构建的贝叶斯网络。
贝叶斯网络结构通常只使用数据,从空网络或naïve贝叶斯结构开始构建。很多时候,在一些领域,比如医学,先验结构知识是已知的。可以自动或手动地对该结构进行细化,以寻找更好的性能模型。在这项工作中,我们采用由专家构建的贝叶斯网络,并表明对该原始网络的微小扰动可以以非常小的计算成本产生更好的分类器,同时保持原始模型的大部分预期意义。
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