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Mining classification rules using rough sets and neural networks

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  • Li, Renpu
  • Wang, Zheng-ou

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  • Li, Renpu & Wang, Zheng-ou, 2004. "Mining classification rules using rough sets and neural networks," European Journal of Operational Research, Elsevier, vol. 157(2), pages 439-448, September.
    • Handle: RePEc:eee:ejores:v:157:y:2004:i:2:p:439-448
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    References listed on IDEAS

    as
    1. Beynon, Malcolm, 2001. "Reducts within the variable precision rough sets model: A further investigation," European Journal of Operational Research, Elsevier, vol. 134(3), pages 592-605, November.
    2. Mak, Brenda & Munakata, Toshinori, 2002. "Rule extraction from expert heuristics: A comparative study of rough sets with neural networks and ID3," European Journal of Operational Research, Elsevier, vol. 136(1), pages 212-229, January.
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    Cited by:

    1. Pantelis Longinidis & Panagiotis Symeonidis, 2013. "Corporate Dividend Policy Determinants: Intelligent Versus A Traditional Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(2), pages 111-139, April.
    2. Derhami, Shahab & Smith, Alice E., 2017. "An integer programming approach for fuzzy rule-based classification systems," European Journal of Operational Research, Elsevier, vol. 256(3), pages 924-934.
    3. Abbas Mardani & Mehrbakhsh Nilashi & Jurgita Antucheviciene & Madjid Tavana & Romualdas Bausys & Othman Ibrahim, 2017. "Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature," Complexity, Hindawi, vol. 2017, pages 1-33, October.
    4. Azam, Nouman & Zhang, Yan & Yao, JingTao, 2017. "Evaluation functions and decision conditions of three-way decisions with game-theoretic rough sets," European Journal of Operational Research, Elsevier, vol. 261(2), pages 704-714.
    5. Baykasoglu, Adil & Ozbakir, Lale, 2007. "MEPAR-miner: Multi-expression programming for classification rule mining," European Journal of Operational Research, Elsevier, vol. 183(2), pages 767-784, December.
    6. Kuang-Hua Hu & Sin-Jin Lin & Ming-Fu Hsu, 2018. "A Fusion Approach for Exploring the Key Factors of Corporate Governance on Corporate Social Responsibility Performance," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
    7. Hou, Zhijian & Lian, Zhiwei & Yao, Ye & Yuan, Xinjian, 2006. "Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique," Applied Energy, Elsevier, vol. 83(9), pages 1033-1046, September.

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