Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes-Reference-Cited by-同舟云学术

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Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes

Published:2013-04-12 Issue:1 Volume:216 Page:163-189
ISSN:0254-5330
Container-title:Annals of Operations Research
language:en
Short-container-title:Ann Oper Res

Author:

Huang Chun-Che,Tseng Tzu-Liang,Jiang Fuhua,Fan Yu-Neng,Hsu Chih-Hua

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,General Decision Sciences

Link

http://link.springer.com/content/pdf/10.1007/s10479-013-1352-1.pdf

Reference39 articles.

1. Ahn, B. S., Cho, S. S., & Kim, C. Y. (2000). The integrated methodology of rough set theory and artificial neural network for business failure prediction. Expert Systems with Applications, 18(2), 65–74.

2. Asharaf, S., Narasimha Murty, M., & Shevade, S. K. (2006). Rough set based incremental clustering of interval data. Pattern Recognition Letters, 27(6), 515–519.

3. Błaszczyński, J., & Słowiński, R. (2003). Incremental induction of decision rules from dominance-based rough approximations. Electronic Notes in Theoretical Computer Science, 82(4), 40–51.

4. Fan, Y.-N., Tseng, T.-L., Chern, C.-C., & Huang, C.-C. (2009). Rule induction based on an incremental rough set. Expert Systems with Applications, 36(9), 11439–11450.

5. Goh, C., & Law, R. (2003). Incorporating the rough sets theory into travel demand analysis. Tourism Management, 24(5), 511–517.

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