An improved algorithm for attribute reduction based on rough sets
一种基于rough集的属性约简的改进算法

At present, basically all attribute reduction based on Rough Sets is to extract the attribute core through the discernbility matrix, then calculate attribute reduction, but the method is still complex. This paper proposed and analyzed an attribute reduction algorithm of weighted mean attribute significance. The algorithm not only can get a reduction, but also does not need core calculating. It can reduce the computing effort and improve the computing efficiency. The algorithm is verified with the instance.