基于遗传算法的Parzen窗离散化方法

为解决连续属性无法直接用于粗糙集理论中这一问题,将Parzen窗方法和遗传算法相结合,提出了一种全新的属性离散化方法。该方法首先选取较多个断点将连续属性分为较多类,然后结合粗糙集理论的一致性要求和Parzen窗所反映的离散结果稳定性指标定义遗传算法的适值函数。仿真结果表明:使用该方法得到的离散结果能得到较少个断点,并且保持数据原有的分类能力。

A Discretization Approach of Parzen Windows Based on GA

To deal with the problem that continuous value can't be applied to the rough set theory(directly),a new attribute discretization approach applying Parzen windows and genetic algorithm(GA) is proposed.Parzen windows which can describe the data distribution status provides stability index of the results for continuous value discretization.Many cutpoints are chosen to classify the continuous values at the beginning,then the consistency requirement of rough set theory and the stability index of Parzen windows are used to define the fitness function of GA.The simulation results show that just a few cutpoints can keep the consistency of knowledge base classification and the stability index is good as well.