The Research of Feature Selection of Text Classification Based on Integrated Learning Algorithm

机译：基于集成学习算法的文本分类特征选择研究

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摘要

Feature selection is a very important step in text classification, which affects the accuracy and validity in text classification. Base on four classic feature selection algorithms of text mining, this paper has established a kind of integrated learning algorithm which applies with feature selection in text classification, in order to improve the accuracy of text classification. Test results show that the algorithm improves the accuracy of text classification.

机译：特征选择是文本分类中非常重要的一步，它影响文本分类的准确性和有效性。基于四种经典的文本挖掘特征选择算法，建立了一种将特征选择应用于文本分类的集成学习算法，以提高文本分类的准确性。测试结果表明，该算法提高了文本分类的准确性。

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来源
《2011 Tenth International Symposium on Distributed Computing and Applications to Business, Engineering and Science》|2011年|p.20-22|共3页
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作者
Huosong Xia; Jian Liu;
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正文语种
中图分类 TP338.84;
关键词
Feature selection; Integrated Learning Algorithm(ILA); Text Classification; The Weights Of Feature;

机译：特征选择集成学习算法文本分类特征权重;

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4. The Research of Feature Selection of Text Classification Based on Integrated Learning Algorithm [C] . Huosong Xia, Jian Liu International Symposium on Distributed Computing and Applications to Business, Engineering and Science . 2010

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The Research of Feature Selection of Text Classification Based on Integrated Learning Algorithm

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