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Several Approaches to Variable Selection by Means of Genetic Algorithms
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Author(s): Marcos G. Pose (University of A Coruna, Spain), Alberto C. Carollo (University of A Coruna, Spain), José M.A. Garda (University of A Coruna, Spain)and Mari P. Gomez-Carracedo (University of A Coruna, Spain)
Copyright: 2006
Pages: 25
Source title:
Artificial Neural Networks in Real-Life Applications
Source Author(s)/Editor(s): Juan R. Rabuñal (University of A Coruña, Spain)and Julian Dorado (University of A Coruña, Spain)
DOI: 10.4018/978-1-59140-902-1.ch007
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Abstract
This chapter shows several approaches to determine how the most relevant subset of variables can perform a classification task. It will permit the improvement and efficiency of the classification model. A particular technique of evolutionary computation, the genetic algorithms, is applied which aim to obtain a general method of variable selection where only the fitness function will be dependent on the particular problem. The solution proposed is applied and tested on a practical case in the field of analytical chemistry to classify apple beverages.
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