基于邻域量化容差关系粗糙集模型的特征选择算法

摘要

数值型不完备信息系统的特征选择方法大多是以容差关系为基础,但是这种处理方式存在数据相似性刻画过于宽松的缺陷.文中提出邻域量化容差关系的粗糙集模型,在该模型的基础上定义邻域量化容差条件熵,分析相关性质,根据邻域量化容差条件熵的单调性构造相应的特征选择算法.实验表明,文中算法在特征选择结果、运行时间和分类精度方面具有优越性.%The existing methods of feature selection are mostly based on tolerance relation in the numerical incomplete information system.However,the data similarity characterization is too loose in these approaches.Therefore,the rough set model of neighborhood valued tolerance relation is proposed in this paper.The neighborhood valued tolerance condition entropy is defined on the basis of the model.And the related properties are analyzed.Finally,the corresponding algorithm is constructed according to the monotonicity of neighborhood valued tolerance condition entropy.Experimental results show that the proposed algorithm is superior to the existing algorithms in terms of the feature selection results,arithmetic operation time and classification accuracy.