DocumentCode
468140
Title
An Efficient Method for Attribute Reduction in Incomplete Information Systems
Author
Li, Renpu ; Zhao, Yongsheng ; Zhang, Fuzeng ; Song, Lihua
Author_Institution
Ludong Univ., Yantai
Volume
1
fYear
2007
fDate
24-27 Aug. 2007
Firstpage
352
Lastpage
356
Abstract
Attribute reduction is an important issue of data mining. In this paper a novel method based on rough sets is provided for attribute reduction in incomplete information systems. Through a transformation technique, an incomplete system is firstly converted into a new and simpler system and then reducts are obtained from the transformed system. It is proved by theorem that the transformed system has the same reducts as the previous one. Experiments show that the proposed method is more efficient on reduct computation of incomplete information systems.
Keywords
data mining; rough set theory; attribute reduction; data mining; incomplete information systems; rough sets; transformed system; Computer science; Data mining; Information systems; Machine learning; Rough sets; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2874-8
Type
conf
DOI
10.1109/FSKD.2007.152
Filename
4405946
Link To Document