贝叶斯网络分类器是数据挖掘与知识发现领域研究的主要方法之一。

Bayesian network classifier is one of the main research methods in data mining and KDD domain.

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主要介绍了贝叶斯网络分类器中的TAN分类器的模型、构造方法及分类方法。

This paper mainly introduces the TAN classifier model, its building method and class method.

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基于基本粗糙集合理论中属性不精确或部分依赖关系的定义，提出了一种新的选择性受限树型贝叶斯网络分类器。

A variant of TAN using rough sets theory is presented, and their tree classifier structures, which can be thought of as a selective restricted trees Bayesian classifier, are compared.

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