Application of a genetic algorithm to feature selection under full validation conditions and to outlier detection

Genetic algorithms have been proved to be a very efficient method in the feature selection problem. However, as for every other method, if the validation of the results is performed in an incomplete way, erroneous conclusions can be drawn. In this paper a development of a previous genetic algorithm is presented so that a full validation of the results can be obtained. Furthermore, this algorithm has been shown to perform very well also as an outlier detector, allowing easy identification of the presence of outliers even in cases where the ‘classical’ techniques fail.