Feature subset selection using a genetic algorithm

被引：686
|
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
收藏
页码：44 / 49
页数：6
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