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Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy

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  • Foster D.P.
  • Stine R.A.

Abstract

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  • Foster D.P. & Stine R.A., 2004. "Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 303-313, January.
  • Handle: RePEc:bes:jnlasa:v:99:y:2004:p:303-313
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    Cited by:

    1. repec:phd:pjdevt:pjd_2005_vol__xxxii_no__1-d is not listed on IDEAS
    2. Margherita Doria & Elisa Luciano & Patrizia Semeraro, 2022. "Machine learning techniques in joint default assessment," Papers 2205.01524, arXiv.org, revised Sep 2023.
    3. Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
    4. Barrios, Erniel B. & Mina, Christian D., 2009. "Profiling Poverty with Multivariate Adaptive Regression Splines," Discussion Papers DP 2009-29, Philippine Institute for Development Studies.
    5. E.B. Nkemnole & A.A. Akinsete, 2021. "Hidden Markov Model using transaction patterns for ATM card fraud detection," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(629), W), pages 51-70, Winter.
    6. Carlos Serrano-Cinca & Begoña Gutiérrez-Nieto, 2011. "Partial Least Square Discriminant Analysis (PLS-DA) for bankruptcy prediction," Working Papers CEB 11-024, ULB -- Universite Libre de Bruxelles.
    7. Barrios, Erniel B. & Mina, Christian D., 2009. "Profiling Poverty with Multivariate Adaptive Regression Splines," Discussion Papers DP 2009-29, Philippine Institute for Development Studies.

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