DocumentCode
2481715
Title
Study on condition attributes and decision attribute based on rough sets theory
Author
Kong, Zhi ; Luan, Haoli ; Gao, Liqun ; Wang, Lifu ; Lu, Zhiguang
Author_Institution
Inf. Sci. & Eng., Northeastern Univ., Shenyang
fYear
2008
fDate
25-27 June 2008
Firstpage
2044
Lastpage
2047
Abstract
The attributes of rough set play an important roles in rough theory. We discussed attribute subdivision in this paper. In the attribute subdivision we mainly research the relationship between attribute subdivision and the upper approximation, lower approximation, quality of approximation classification, accuracy of approximation classification, number of decision rules and relative reduction. Meanwhile, the qualities of non-redundant and redundant attributes are analyzed. In the decision subdivision, the attribute subdivision and decision subdivision are studied in the same decision table. Finally, an example is shown to understand the above properties. The research is helpful for the attribute reduction, formation of decision rules and enhancing confidences of decision rules.
Keywords
rough set theory; approximation classification accuracy; approximation classification quality; attribute subdivision; condition attributes; decision attribute; decision rules; decision subdivision; decision table; lower approximation; nonredundant attributes; redundant attributes; relative reduction; rough sets theory; upper approximation; Artificial intelligence; Automation; Data mining; Engineering management; Heat engines; Intelligent control; Knowledge acquisition; Pattern recognition; Rough sets; Set theory; Approximation accuracy; Approximation quality; Attribute subdivision; Decision subdivision; Rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4593239
Filename
4593239
Link To Document