Title :
Uncertainty Measure of Covering Generated Rough Set
Author :
Hu, Jun ; Wang, Guoyin ; Qinghua Zhang
Author_Institution :
Sch. of Electron. Eng., Xidian Univ., Xi´´an
Abstract :
Uncertainty measure is a key issue of knowledge discovery based on covering approximation space. Information entropy was applied into both classical rough set and extended rough set to measure the uncertainty respectively, but their relationship has not been studied. Based on equal domain relation, a covering approximation space is converted into a partition approximation space in this paper, and uncertainty measures of covering generated rough set are developed. Their properties are analyzed with the generated partition approximation space fined, and these properties are still kept with the original covering approximation spacer fined
Keywords :
approximation theory; data mining; entropy; rough set theory; covering generated rough set; information entropy; knowledge discovery; partition approximation space; uncertainty measure; Computer science; Extraterrestrial measurements; Information analysis; Information entropy; Information systems; Intelligent agent; Knowledge engineering; Measurement uncertainty; Set theory; Space technology;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2749-3
DOI :
10.1109/WI-IATW.2006.139
