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
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;
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
DOI :
10.1109/WCICA.2008.4593239