Feature subset selection using a genetic algorithm

被引：710

作者：

Yang, JH ^{[1
]}

Honavar, V

机构：

[1] Iowa State Univ, Dept Comp Sci, AI Res Grp, Ames, IA 50011 USA

[2] Iowa State Univ, Artificial Intelligence Res Lab, Ames, IA 50011 USA

来源：

IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS | 1998年 / 13卷 / 02期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1109/5254.671091

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Practical pattern-classification and knowledge-discovery problems require the selection of a subset of attributes or features to represent the patterns to be classified. The authors' approach uses a genetic algorithm to select such subsets, achieving multicriteria optimization in terms of generalization accuracy and costs associated with the features.

引用

页码：44 / 49

页数：6

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