A feature ranking model with redundancy control

被引：0
作者：
Zhou X. [1 ]
Diao X. [2 ]
Cao J. [2 ]
机构：
[1] School of Command Info. System, PLA Univ. of Sci. and Technol., Nanjing
[2] Nanjing Inst. of Telecommunications Technol., Nanjing
来源：
Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) | 2016年 / 48卷 / 05期
关键词：
Feature ranking; Feature redundancy; Feature selection; Nonlinear programming;
D O I：
10.15961/j.jsuese.2016.05.021
中图分类号：
学科分类号：
摘要：
Aimed at problems of feature redundancy caused by the fact that feature correlation was seldom considered in the feature ranking methods, a feature ranking model with redundancy control was proposed. Maximum discrimination ability and minimum redundancy of a feature subset were used as the objective functions of the very model so as to reduce the redundancy among features, and greed and non-linear programming methods were employed to solve the model. Experiments were conducted on 9 public datasets and compared with feature ranking, and the result showed that the model can obtain a better classification accuracy and less feature size on most datasets. When non-linear programming method is employed, the model can yield a feature subset, on benefit for determining the feature size. This model can be used when correlation exists among features. © 2016, Editorial Department of Journal of Sichuan University (Engineering Science Edition). All right reserved.
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页码：153 / 158
页数：5
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