A Novel Attribute Reduction Algorithm Based on GA
Attribute reduction is a key problem for the rough set theory and to solve the minimum reduction belongs to the NP-Hard problem.In order to achieve effectively relative attribute reduction,proposes a rough set attribute reduction algorithm based on GA.The core is joined initial population in GA in order to accelerate capacity.And introduces the dependence degree of decision attribute in the condition attribute in the fitness function,so as the algorithm can not only ensure the global optimization performance but strengthen the local search ability,obtain optimal search performacnce.Experiential result shows the algorithm is fast and effective.