DocumentCode
493469
Title
Attribute Reduction Based on Rough Neighborhood Approximation
Author
He, Ming ; Du, Yong-ping
Author_Institution
Dept. of Comput. Sci., Beijing Univ. of Technol., Beijing
Volume
1
fYear
2009
fDate
7-8 March 2009
Firstpage
343
Lastpage
345
Abstract
One of the main obstacles facing current data mining techniques is attribute reduction. This paper discusses the basic concepts of rough set, and studies two rough approximations operators under neighborhood systems. An attribute reduction method based on rough set theory and neighborhood systems is presented. The experimental results show that the method of attributes reduction with rough sets and neighborhood system is feasible and valid.
Keywords
approximation theory; data mining; rough set theory; attribute reduction method; data mining techniques; rough neighborhood approximation; rough set theory; Artificial intelligence; Computer science; Computer science education; Data mining; Educational technology; Helium; Information systems; Pattern recognition; Rough sets; Set theory; approximation; attribute reduction; neighborhood systems; rough set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-1-4244-3581-4
Type
conf
DOI
10.1109/ETCS.2009.85
Filename
4958788
Link To Document