Title :
Feature subset selection using a genetic algorithm
Author :
Yang, Jihoon ; Honavar, Vasant
Author_Institution :
Iowa State Univ., Ames, IA, USA
Abstract :
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
Keywords :
generalisation (artificial intelligence); genetic algorithms; knowledge acquisition; pattern classification; feature subset selection; generalization accuracy; genetic algorithm; knowledge-discovery; multicriteria optimization; pattern-classification; Blood; Costs; Genetic algorithms; Large-scale systems; Medical diagnosis; Medical tests; Neural networks; Performance evaluation; Surgery; Testing;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.671091
