ARGEN + AREPO: mixing the artificial genetic engineering and artificial evolution of populations to improve the search process

In this paper we analyze the performance of several evolutionary algorithms in the feature and instance selection problem. It is also introduced the ARGEN + AREPO search algorithm which has been tested in the same problem. There is no need to adapt parameters in this genetic algorithm, except the population size. The reported preliminary results show that using this technique in a wrapper model to search data subsets, we can obtain accuracy similar to the obtained with some of the genetic algorithms models here presented, but with less data.