Research on Feature Selection of Multi-Objective Optimization

被引：2

作者：

Zhang, Mengting ^{[1
]}

Du, Jianqiang ^{[1
]}

Luo, Jigen ^{[1
]}

Nie, Bin ^{[1
]}

Xiong, Wangping ^{[1
]}

Liu, Ming ^{[1
]}

Zhao, Shuhan ^{[1
]}

机构：

[1] College of Computer Science, Jiangxi University of Traditional Chinese Medicine, Nanchang

来源：

Computer Engineering and Applications | 2024年 / 59卷 / 03期

关键词：

evolutionary algorithms; feature selection; multi-objective optimization;

D O I：

10.3778/j.issn.1002-8331.2206-0230

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Feature selection is an effective dimensionality reduction method in the field of pattern recognition. When multiple objectives involved in feature selection conflict with each other and are difficult to balance, it is a research hotspot to regard feature selection as a multi-objective optimization problem. In order to facilitate researchers to systematically understand the research status and development trend in the field of multi-objective feature selection, this paper reviews the methods of multi-objective feature selection. This paper clarifies the nature of feature selection and multi-objective optimization. According to the differences and characteristics of multi-objective optimization methods, it focuses on the advantages and disadvantages of various multi-objective optimization feature selection methods. It discusses the existing multi-objective optimization feature selection research methods problems and prospects for the future. © 2024 Journal of Computer Engineering and Applications Beijing Co., Ltd.; Science Press. All rights reserved.

引用

页码：23 / 32

页数：9

共 61 条

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