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
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;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2011 2nd International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-0813-8
DOI :
10.1109/ICICIP.2011.6008253