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 :
بازگشت