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Study of E-mail Filtering Based on Mutual Information Text Feature Selection Method

机译:基于互信息文本特征选择方法的电子邮件过滤研究

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Aiming at the problem with filtering E-mail, based on analyzing defects of the traditional mutual information , an approach based on quadratic TF * IDF mutual information feature selection is presented in the paper; then the importance of characteristic words appearing just in only one class is again measured to solve the problem that feature selection is not effectively done because of equal mutual information value. Finally, Bayesian classifier is used for experiment and experimental result shows that compared with the original method, the presented approach possesses higher correct rate and more efficiency of classification in text classification.
机译:针对电子邮件过滤的问题,在分析传统互信息的缺陷的基础上,提出了一种基于二次TF * IDF互信息特征选择的方法。然后再次测量仅出现在一个类别中的特征词的重要性,以解决由于相等的互信息值而不能有效地进行特征选择的问题。最后,使用贝叶斯分类器进行实验,实验结果表明,与原始方法相比,该方法在文本分类中具有较高的正确率和较高的分类效率。

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