Several Approaches to Variable Selection by Means of Genetic Algorithms
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
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.