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Proceedings Paper

An uncertainty algorithm for multivariate decision tree construction
Author(s): Yun-fei Qiu; Xu E; Liang-shan Shao; Shao-guang Sun
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Paper Abstract

Aimed at the problem of the inability for multivariable decision tree algorithm to effectively deal with noisy data, the paper extends the relative core of attributes in rough sets theory to variable precision rough set (VPRS), and uses it for selection of initial variables for decision tree. The paper extends the concept of generalization of one equivalence relation with respect to another one, to relative generalization equivalence relation under mostly-contained condition, and uses it for decision tree initial attribute check. Finally, we propose an algorithm for multivariable decision tree that can avoid disturbance of noisy data.

Paper Details

Date Published: 11 July 2009
PDF: 7 pages
Proc. SPIE 7490, PIAGENG 2009: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 74901T (11 July 2009); doi: 10.1117/12.836681
Show Author Affiliations
Yun-fei Qiu, Liaoning Technical Univ. (China)
Xu E, Liaoning Univ. of Technology (China)
Liang-shan Shao, Liaoning Technical Univ. (China)
Shao-guang Sun, Liaoning Technical Univ. (China)


Published in SPIE Proceedings Vol. 7490:
PIAGENG 2009: Intelligent Information, Control, and Communication Technology for Agricultural Engineering

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