Application of variable precision Rough Set Attribute Reduction Algorithm

摘要：

In order to remove the drawbacks of the classical attribute reduction algorithm based on attribute importance which cant ensure to gain the simplest decision table and the best noise resisting ability, this paper presents a improved attribute reduction algorithm based onβ-variable precision rough sets. A parameter β represents the error resolution and makes the decision table more simple and reliable. Compared with the classical attribution reduction algorithm,β variable precision rough sets attribute reduction algorithm has better generalization and ability of resisting noise. These two algorithms are used on the simulation of Car Test Results and the results verify the superiority of the improved algorithm.

关键词： attribute reduction rough sets variable precision

作者: Zhang Cai-yun Wang Jing Wang Hui

作者单位: National Engineer Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 687-691

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）