Feature selection algorithm based on Levy flight

Abstract

A Levy flight random process based feature selection algorithm(LevyFS) was proposed in order to improve the speed of feature selection method.A multi-stages heuristic search strategy was defined during optimization process.Levy flight random process was introduced in local search behavior,and map between Levy flight distances and search operations was defined.During different search stages,map was used to change the probability of search behavior so as to control the direction and speed of local search behavior.Then local optimum was prevented.Experimental results show that LevyFS algorithm overcomes the limitation of heuristic methods and the average time cost of LevyFS algorithm is only one-third time cost of SFFS algorithm.