An improved global feature selection scheme for text classification
作者：
Highlights：
• An improved global feature selection scheme is proposed for text classification.
• It is an ensemble method combining the power of two filter-based methods.
• The new method combines a global and a one-sided local feature selection method.
• By incorporating these methods, the feature set represents classes almost equally.
• This method outperforms the individual performances of feature selection methods.
摘要
•An improved global feature selection scheme is proposed for text classification.•It is an ensemble method combining the power of two filter-based methods.•The new method combines a global and a one-sided local feature selection method.•By incorporating these methods, the feature set represents classes almost equally.•This method outperforms the individual performances of feature selection methods.
论文关键词：Global feature selection,Filter,Text classification,Pattern recognition
论文评审过程：Received 23 April 2015, Revised 28 August 2015, Accepted 29 August 2015, Available online 6 September 2015, Version of Record 20 October 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.08.050
