DocumentCode :
2919694
Title :
The Attribute Reduce with SAT Algorithm
Author :
Zhao, Qingshan ; Zheng, Xiaolong
Author_Institution :
Dept. of Comput., Shanxi Xinzhou Teachers Univ., Xinzhou, China
Volume :
3
fYear :
2009
fDate :
21-22 Nov. 2009
Firstpage :
23
Lastpage :
26
Abstract :
Rough set theory has been successfully applied to many areas including machine learning pattern recognition decision analysis process control, knowledge discovery from databases. An algorithm in finding minimal reduction based on prepositional satisfiability (abbreviated as SAT) algorithm is proposed. A branch and bound algorithm is presented to solve the proposed SAT problem. The experimental result shows that the proposed algorithm has significantly reduced the number of rules generated form the obtained reduction with high percentage of classification accuracy.
Keywords :
computability; rough set theory; tree searching; SAT algorithm; branch-and-bound algorithm; minimal attribute reduction; prepositional satisfiability; rough set theory; Algorithm design and analysis; Data analysis; Databases; Decision making; Information analysis; Information systems; Machine learning algorithms; Pattern analysis; Pattern recognition; Rough sets; SAt; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
Type :
conf
DOI :
10.1109/IITA.2009.347
Filename :
5369560
Link To Document :
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