基于相似粗糙集的案例特征权值确定新方法

A New Approach Based on Similarity Rough Set for Determining Case Feature Weights

针对现有案例特征权值确定方法客观性差、算法复杂等问题,首先介绍和完善了基于传统粗糙集的权值确定方法.其次,针对基于传统粗糙集的方法会造成案例相似度测量误差从而影响案例推理的准确性的问题,将传统粗糙集的不可分辨关系推广为相似关系,提出了一种基于相似粗糙集的案例特征权值确定方法.给出了相似粗糙集的基本定义,以及利用该方法基于差别矩阵进行特征权值计算的两个定理.最后,用实例表明了方法的有效性.*

A method based on the classical rough set （CRS） for determining the case feature weights is introduced and improved in order to overcome problems of the existing algorithms such as poor objectivity and high complexity. For the problem that the accuracy of case-based reasoning （CBR） degrades due to measurement errors of the case similarity caused by the CRS methods, a new method based on similarity rough set （SRS） for determining the case feature weights is proposed where the indiscernibility relation is extended to the similarity relation of the CRS. The definitions of SRS and two theorems of computing the feature weights based on discernibility matrix are presented. And the proposed methods are proved to be effective with a practical example.