Use of Multiobjective Genetic Algorithms in Feature Selection

The intelligent analysis of Databases may be affected by the presence of unimportant features, which motivates the application of Feature Selection. By treating this task as a search and optimization process, it is possible to use the synergy between Genetic Algorithms and Multi-objective Optimization to carry out the search for (quasi) optimal subsets of features considering possible conflicting importance criteria. This work presents an application of Multi-objective Genetic Algorithms to the Feature Selection problem, combining different criteria measuring the importance of the subsets of features.