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Rule extraction from expert heuristics: A comparative study of rough sets with neural networks and ID3

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  • Mak, Brenda
  • Munakata, Toshinori

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  • 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.
    • Handle: RePEc:eee:ejores:v:136:y:2002:i:1:p:212-229
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    References listed on IDEAS

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    1. Hashemi, R. R. & Le Blanc, L. A. & Rucks, C. T. & Rajaratnam, A., 1998. "A hybrid intelligent system for predicting bank holding structures," European Journal of Operational Research, Elsevier, vol. 109(2), pages 390-402, September.
    2. Slowinski, R. & Zopounidis, C. & Dimitras, A. I., 1997. "Prediction of company acquisition in Greece by means of the rough set approach," European Journal of Operational Research, Elsevier, vol. 100(1), pages 1-15, July.
    3. R. Slowinski & C. Zopounidis, 1995. "Application of the Rough Set Approach to Evaluation of Bankruptcy Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(1), pages 27-41, March.
    4. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    5. Salonen, Hannu & Nurmi, Hannu, 1999. "A note on rough sets and common knowledge events," European Journal of Operational Research, Elsevier, vol. 112(3), pages 692-695, February.
    6. Pawlak, Zdzisaw & Sowinski, Roman, 1994. "Rough set approach to multi-attribute decision analysis," European Journal of Operational Research, Elsevier, vol. 72(3), pages 443-459, February.
    7. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 1999. "Rough approximation of a preference relation by dominance relations," European Journal of Operational Research, Elsevier, vol. 117(1), pages 63-83, August.
    8. Pawlak, Zdzislaw, 1997. "Rough set approach to knowledge-based decision support," European Journal of Operational Research, Elsevier, vol. 99(1), pages 48-57, May.
    9. Nurmi, Hannu & Kacprzyk, Janusz & Fedrizzi, Mario, 1996. "Probabilistic, fuzzy and rough concepts in social choice," European Journal of Operational Research, Elsevier, vol. 95(2), pages 264-277, December.
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    Cited by:

    1. de Andres, Javier & Landajo, Manuel & Lorca, Pedro, 2005. "Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case," European Journal of Operational Research, Elsevier, vol. 167(2), pages 518-542, December.
    2. Ching-Hsue Cheng & Ssu-Hsiang Wang, 2015. "A quarterly time-series classifier based on a reduced-dimension generated rules method for identifying financial distress," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1979-1994, December.
    3. Thomassey, Sébastien, 2010. "Sales forecasts in clothing industry: The key success factor of the supply chain management," International Journal of Production Economics, Elsevier, vol. 128(2), pages 470-483, December.
    4. Navin K. Dev & Ravi Shankar & Angappa Gunasekaran & Lakshman S. Thakur, 2016. "A hybrid adaptive decision system for supply chain reconfiguration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7100-7114, December.
    5. 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.
    6. De Angelis, Vanda & Felici, Giovanni & Impelluso, Paolo, 2003. "Integrating simulation and optimisation in health care centre management," European Journal of Operational Research, Elsevier, vol. 150(1), pages 101-114, October.

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