An improved combination feature selection based on ReliefF and genetic algorithm

Feature selection is a hot topic in current information science, especially in the field of pattern recognition. In this paper, a combination feature selection Algorithm, ReGA, which merges the feature selection technique, ReliefF, into Genetic Algorithms Method, is presented. Experiments show that the new method improves the fitness of initial population, it can find the optimal solution more quickly, and improve the efficiency of SGA.