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
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;
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
DOI :
10.1109/ETCS.2009.85
