Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem

The feature selection problem has been usually addressed through heuristic approaches given its significant computational complexity. In this context, evolutionary techniques have drawn the researchers’ attention owing to their appealing optimization capabilities. In this chapter, promising results achieved by the authors in solving the feature selection problem through a joint effort between rough set theory and evolutionary computation techniques are reviewed. In particular, two new heuristic search algorithms are introduced, i.e. Dynamic Mesh Optimization and another approach which splits the search process carried out by swarm intelligence methods.