关键词: 粗糙集, 属性约简, 分辨矩阵, 加权浓缩树, 空间复杂度

Abstract: Focused on the issue that there are redundant elements in the algorithm based on the discernibility matrix, which leads to the high cost of space storage, an attribute reduction algorithm based on weighted condensed tree is proposed in this paper. The algorithm can further eliminate the redundant elements, compress the information in the discernibility matrix, and consider the effect of attribute importance in the process of constructing the tree structure. The experimental results are compared with the C-Tree and the discernibility information tree algorithm. The proposed algorithm can obtain better attribute reduction results, which can effectively reduce the space complexity.

Key words: rough set, attribute reduction, discernibility matrix, weighted condensed tree, space complexity