Neighborhood Rough Set Model in Incomplete Information System
There is a large number of Incomplete continuous data in real life and classical rough set theory is only available for discrete data. In such a case, a new neighborhood rough set model for incomplete information system is proposed to classify the objects by using the distance set of attribute value. It is proved that neighborhood relation is equivalent to the similarity relation when threshold value is zero, and neighborhood relation also has the same meaning with indiseernibility relation on the condition that the information system is complete and threshold value is zero. A heuristic knowledge reduct algorithm based on neighborhood relation is provided and an example of knowledge reduct to several different information systems confirms the effectiveness of neighborhood rough set model for incomplete information system.
Incomplete information system rough set neighborhood relation continuous value
Ping Li Xin Lu Qi-zong Wu
School of Management and Economies Beijing Institute of Technology Beijing, China
国际会议
The 10th International Conference on Intelligent Technologies(第十届智慧科技国际会议 InTech09)
桂林
英文
548-553
2009-12-12（万方平台首次上网日期，不代表论文的发表时间）