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Proceedings Paper

A new heuristic reduction algorithm based on general binary relations
Author(s): Shuhua Teng; Jixiang Sun; Zhiyong Li; Gang Zou
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Paper Abstract

Firstly, the concepts of discernibility degree and relative discernibility degree are presented based on general binary relations. Then the properties of these concepts are analyzed. Furthermore, an efficient attribute reduction algorithm is designed based on the relative discernibility degree. Especially, the attribute reduction algorithm is able to deal with various kinds of extended models of classical rough set theory, such as the tolerance relation-based rough set model, non-symmetric similarity relation-based rough set model. Finally, the theoretical analysis is backed up with numerical examples to prove that the proposed reduction method is an effective technique to select useful features and eliminate redundant and irrelevant information.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 749629 (30 October 2009); doi: 10.1117/12.832682
Show Author Affiliations
Shuhua Teng, National Univ. of Defense Technology (China)
Jixiang Sun, National Univ. of Defense Technology (China)
Zhiyong Li, National Univ. of Defense Technology (China)
Gang Zou, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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