Rough Set Attribute Reduction Algorithm Based on Immune Genetic Algorithm

摘要

In this paper, we propose a kind of rough set attribute reduction algorithm which is based on immune genetic algorithm. It adopts adaptive crossover and mutation operators, uses the step by step evolution tactics based on shrinking precision as the stop criterion. The experiment proves that the algorithm is effective, it has improved the global search ability to avoid falling into local optimum, and it can quickly get relative minimum attribute reduction.