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.
Effects of variable selection and processing of NIR and ATR-IR spectra on the prediction of extractive content in Eucalyptus bosistoana heartwood
