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

Author

Huosong, Xia ; Jian, Liu

Author_Institution

Dept. of Coll. of Econ. & Manage., Wuhan Textile Univ., Wuhan, China

fYear

2011

fDate

14-17 Oct. 2011

Firstpage

20

Lastpage

22

Abstract

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.

Keywords

data mining; learning (artificial intelligence); pattern classification; text analysis; feature selection; integrated learning algorithm; text classification; text mining algorithm; Accuracy; Classification algorithms; Educational institutions; Machine learning algorithms; Support vector machines; Text categorization; Training; Feature selection; Integrated Learning Algorithm(ILA); Text Classification; The Weights Of Feature;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing and Applications to Business, Engineering and Science (DCABES), 2011 Tenth International Symposium on

Conference_Location

Wuxi

Print_ISBN

978-1-4577-0327-0

Type

conf

DOI

10.1109/DCABES.2011.95

Filename

6119048