DocumentCode :
547447
Title :
Research on attribute reduction based on variable precision rough sets model
Author :
Wang, Xiaoyan ; Yang, Sichun ; Ji, Bin
Author_Institution :
Sch. of Comput. Sci., Anhui Univ. of Technol., Ma´´anshan, China
Volume :
1
fYear :
2011
fDate :
10-12 June 2011
Firstpage :
413
Lastpage :
416
Abstract :
Variable precision rough sets model is an extension of classical rough sets theory and can deal with inconsistent data. Upper and lower distribution reduction are important attribute reduction in rough set. Utilizing distribution function, the paper puts forward some theories about upper and lower distribution reduction and appropriate binary discernable matrix based on Ziarko variable precision rough sets model. That applying logic operation in binary discernable matrix can carry out attribute reduction to variable precision rough sets model, which can solve the problem about upper and lower distribution reduction of inconsistent decision tables effectively.
Keywords :
rough set theory; Ziarko variable precision rough set model; appropriate binary discernable matrix; attribute reduction; decision tables; distribution reduction; logic operation; binary discernable matrix; distribution reduction; inconsistent decision tables; variable precision rough set model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
Type :
conf
DOI :
10.1109/CSAE.2011.5953251
Filename :
5953251
Link To Document :
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