DocumentCode :
2839441
Title :
Feature selection for text classification using OR+SVM-RFE
Author :
Luo, Meixiang ; Luo, Linkai
Author_Institution :
Coll. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
1648
Lastpage :
1652
Abstract :
Feature selection is the key issue in text classification because there are a large number of attributes. In this paper, we propose a new algorithm OR+SVM-RFE that integrates Odds Radio(OR) with recursive feature elimination based on SVM(SVM-RFE). Odds Radio is first used to roughly and rapidly select a feature subset. Then SVM-RFE is used to delicately select a smaller feature subset. Experiment results show the feature subset selected by OR+SVM-RFE obtains a good classification performance with less features.
Keywords :
classification; feature extraction; support vector machines; text analysis; OR+SVM-RFE algorithm; feature selection; feature subset; odds radio; recursive feature elimination; support vector machine; text classification; Classification algorithms; Classification tree analysis; Educational institutions; Information science; Internet; Machine learning; Machine learning algorithms; Support vector machine classification; Support vector machines; Text categorization; Feature Selection; Odds Ratio; SVM-RFE; Text Classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498331
Filename :
5498331
Link To Document :
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