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An approach to generate rules from neural networks for regression problems

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  • Setiono, Rudy
  • Thong, James Y. L.

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  • Setiono, Rudy & Thong, James Y. L., 2004. "An approach to generate rules from neural networks for regression problems," European Journal of Operational Research, Elsevier, vol. 155(1), pages 239-250, May.
    • Handle: RePEc:eee:ejores:v:155:y:2004:i:1:p:239-250
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    References listed on IDEAS

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    1. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    2. James R. Coakley & Carol E. Brown, 1993. "Artificial Neural Networks Applied to Ratio Analysis in the Analytical Review Process," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 2(1), pages 19-39, January.
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    Cited by:

    1. Daniel Santin, 2008. "On the approximation of production functions: a comparison of artificial neural networks frontiers and efficiency techniques," Applied Economics Letters, Taylor & Francis Journals, vol. 15(8), pages 597-600.
    2. Edson Pindza & Jules Clement Mba & Sutene Mwambi & Nneka Umeorah, 2023. "Neural Network for valuing Bitcoin options under jump-diffusion and market sentiment model," Papers 2310.09622, arXiv.org.

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