DocumentCode
3134289
Title
The attribute reduction of the information system based on new rough set
Author
Ma, Minghua ; Deng, Tingquan
Author_Institution
Dept. of Math., Harbin Eng. Univ., Harbin, China
Volume
1
fYear
2011
fDate
25-28 July 2011
Firstpage
301
Lastpage
304
Abstract
Attribute reduction is considered as an important preprocessing step for pattern recognition, machine learning, and data mining. The traditional rough set theory is mainly used to reduce the attributes and keep the lower approximation unchanged. In this paper we first give two forms of new rough sets: object-oriented rough set and attribute-oriented rough set, and then discuss their properties in detail. Based on the new models, this paper studies the attribute reduction of information system. At last it studies the attribute reduction of decision information systems by combining the old rough set and new rough set together.
Keywords
formal concept analysis; information systems; rough set theory; attribute-oriented rough set; data mining; decision information system; formal concept analysis; information system attribute reduction; machine learning; object-oriented rough set; pattern recognition; rough set theory; Approximation methods; Artificial intelligence; Data analysis; Lattices; Rough sets; attribute reduction; information system; rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4577-0813-8
Type
conf
DOI
10.1109/ICICIP.2011.6008253
Filename
6008253
Link To Document