Feature Subset Selection Using a Genetic Algorithm

Jh Yang,V Honavar

IEEE Intelligent Systems（1998）SCI 3区

Iowa State Univ

被引用1488|浏览22

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.

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关键词

generalisation (artificial intelligence),genetic algorithms,knowledge acquisition,pattern classification,feature subset selection,generalization accuracy,genetic algorithm,knowledge-discovery,multicriteria optimization,pattern-classification