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A New Feature Selection Method for Text Classification Based on Independent Feature Space Search
Joint Authors
Liu, Yong
Ju, Shenggen
Wang, Junfeng
Su, Chong
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-12
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Feature selection method is designed to select the representative feature subsets from the original feature set by different evaluation of feature relevance, which focuses on reducing the dimension of the features while maintaining the predictive accuracy of a classifier.
In this study, we propose a feature selection method for text classification based on independent feature space search.
Firstly, a relative document-term frequency difference (RDTFD) method is proposed to divide the features in all text documents into two independent feature sets according to the features’ ability to discriminate the positive and negative samples, which has two important functions: one is to improve the high class correlation of the features and reduce the correlation between the features and the other is to reduce the search range of feature space and maintain appropriate feature redundancy.
Secondly, the feature search strategy is used to search the optimal feature subset in independent feature space, which can improve the performance of text classification.
Finally, we evaluate several experiments conduced on six benchmark corpora, the experimental results show the RDTFD method based on independent feature space search is more robust than the other feature selection methods.
American Psychological Association (APA)
Liu, Yong& Ju, Shenggen& Wang, Junfeng& Su, Chong. 2020. A New Feature Selection Method for Text Classification Based on Independent Feature Space Search. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1196487
Modern Language Association (MLA)
Liu, Yong…[et al.]. A New Feature Selection Method for Text Classification Based on Independent Feature Space Search. Mathematical Problems in Engineering No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1196487
American Medical Association (AMA)
Liu, Yong& Ju, Shenggen& Wang, Junfeng& Su, Chong. A New Feature Selection Method for Text Classification Based on Independent Feature Space Search. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1196487
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196487