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