Genetic algorithms applied to feature selection in PLS regression: how and when to use them

被引:699
作者
Leardi, R
Gonzalez, AL
机构
[1] Univ Genoa, Dipartimento Chim & Tecnol Farmaceut & Alimentari, I-16147 Genoa, Italy
[2] Univ Granada, Fac Ciencias, Dept Quim Analit, Granada, Spain
关键词
genetic algorithms; feature selection; PLS regression;
D O I
10.1016/S0169-7439(98)00051-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Genetic algorithms (GA) are very useful in solving complex problems of optimization. The selection of the best subset of variables is surely one of them. In this paper, a new approach is proposed, and the positive and negative aspects of the application of GA in selecting variables for a partial least squares (PLS) model are taken into account. Finally, the analysis of the results obtained on several real data sets allows to find a rationale for a sensible application, showing that, if correctly applied, this technique almost always produces very good results. (C) 1998 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:195 / 207
页数:13
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