本文对极大或极小数据集下的贝叶斯网络学习进行了研究，并提出了相关的解决方案。

This thesis is about the study on learning Bayesian Network from extremely large or small datasets and its application.

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该方法可避免现有的贝叶斯网络学习过于依赖数据、对数据的数量和质量要求过高等问题。

This method can avoid the problems of depending on a large number of data with high quality in existing Bayesian network learning.

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贝叶斯网络的学习。

The learning of Bayesian Networks.

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