DocumentCode
475940
Title
Approach for absolute attribute reductions in rough sets
Author
Pei, Xiao-Bing
Author_Institution
Coll. of Software, HuaZhong Univ. of Sci. & Technol., Wuhan
Volume
1
fYear
2008
fDate
12-15 July 2008
Firstpage
391
Lastpage
394
Abstract
Attribute reductions is one of the basic contents in rough sets and one of the most problem in knowledge acquisition. At present, the methods used are often Pawlakpsilas data analysis and Skowronpsilas discernible matrix methods. In this paper an approach for the set of all absolute attribute reductions is proposed based on the discernible attribute set. Finally, we also show the experimental results by examples.
Keywords
knowledge acquisition; rough set theory; absolute attribute reductions; data analysis; discernible matrix methods; knowledge acquisition; rough sets; Cybernetics; Data analysis; Educational institutions; Information systems; Knowledge acquisition; Machine learning; NP-hard problem; Rough sets; Set theory; Absolute attribute reduction; Rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620437
Filename
4620437
Link To Document