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

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。

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The results prove that TAN classifier has perfect classification capability and higher classification accuracy.

实验结果表明TAN分类器具有较好的分类性能和较高的分类精度。

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TAN classifier extends the structure of Naive Bayes classifier by adding augmenting arcs that obey certain structural restrictions.

TAN分类器按照一定的结构限制，通过添加扩展弧的方式扩展朴素贝叶斯分类器的结构。

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