DocumentCode
2664110
Title
New heuristic attribute reduction algorithm based on rough set
Author
Weiwei, Fang ; Bingru, Yang ; Zheng, Peng
Author_Institution
Inf. Eng. Sch., Univ. of Sci. & Technol. Beijing, Beijing
fYear
2008
fDate
16-18 July 2008
Firstpage
285
Lastpage
287
Abstract
This paper summarized advantages and disadvantages of recent attribute reduction algorithms, and proposed a new attribute reduction method which is taken attribute correlation as heuristic information, this method can not only remove irrelevant features, but also delete redundant features from the candidate attribute set. Theoretical analysis and experiment results demonstrate that on the premise of unchanged classification precision, the algorithm can obtain the best attribute reduce set and has good feasibility.
Keywords
data mining; rough set theory; data mining; heuristic attribute reduction algorithm; rough set; Algorithm design and analysis; Classification algorithms; Data mining; Glass; Heuristic algorithms; Information science; Voting; Attribute Reduction; Data mining; KDD; Rough Set;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location
Kunming
Print_ISBN
978-7-900719-70-6
Electronic_ISBN
978-7-900719-70-6
Type
conf
DOI
10.1109/CHICC.2008.4605398
Filename
4605398
Link To Document