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Mining the customer credit using classification and regression tree and multivariate adaptive regression splines

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  • Lee, Tian-Shyug
  • Chiu, Chih-Chou
  • Chou, Yu-Chao
  • Lu, Chi-Jie

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  • Lee, Tian-Shyug & Chiu, Chih-Chou & Chou, Yu-Chao & Lu, Chi-Jie, 2006. "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1113-1130, February.
  • Handle: RePEc:eee:csdana:v:50:y:2006:i:4:p:1113-1130
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    References listed on IDEAS

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    3. Piramuthu, Selwyn, 1999. "Financial credit-risk evaluation with neural and neurofuzzy systems," European Journal of Operational Research, Elsevier, vol. 112(2), pages 310-321, January.
    4. Bardos, Mireille, 1998. "Detecting the risk of company failure at the Banque de France," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1405-1419, October.
    5. Wiginton, John C., 1980. "A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(03), pages 757-770, September.
    6. Jagielska, Ilona & Jaworski, Janusz, 1996. "Neural Network for Predicting the Performance of Credit Card Accounts," Computational Economics, Springer;Society for Computational Economics, vol. 9(1), pages 77-82, February.
    7. Desai, Vijay S. & Crook, Jonathan N. & Overstreet, George A., 1996. "A comparison of neural networks and linear scoring models in the credit union environment," European Journal of Operational Research, Elsevier, vol. 95(1), pages 24-37, November.
    8. Barney, Douglas K. & Finley Graves, O. & Johnson, John D., 1999. "The farmers home administration and farm debt failure prediction," Journal of Accounting and Public Policy, Elsevier, vol. 18(2), pages 99-139.
    9. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    10. repec:bla:joares:v:10:y:1972:i:1:p:167-179 is not listed on IDEAS
    11. De Gooijer, Jan G. & Ray, Bonnie K. & Krager, Horst, 1998. "Forecasting exchange rates using TSMARS," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 513-534, June.
    12. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    13. Laitinen, Erkki K., 1999. "Predicting a corporate credit analyst's risk estimate by logistic and linear models," International Review of Financial Analysis, Elsevier, vol. 8(2), pages 97-121, June.
    14. Jae-Chan Kim & Dae-Ho Kim & Jae-Jun Kim & Jong-Suk Ye & Hyun-Soo Lee, 2000. "Segmenting the Korean housing market using multiple discriminant analysis," Construction Management and Economics, Taylor & Francis Journals, vol. 18(1), pages 45-54.
    15. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
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    Cited by:

    1. Kim, Soo Y. & Upneja, Arun, 2014. "Predicting restaurant financial distress using decision tree and AdaBoosted decision tree models," Economic Modelling, Elsevier, vol. 36(C), pages 354-362.
    2. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    3. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015. "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, vol. 30(3), pages 821-843, September.
    4. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    5. Elcin Koc & Cem Iyigun, 2014. "Restructuring forward step of MARS algorithm using a new knot selection procedure based on a mapping approach," Journal of Global Optimization, Springer, vol. 60(1), pages 79-102, September.
    6. Elcin Koc & Cem Iyigun & İnci Batmaz & Gerhard-Wilhelm Weber, 2014. "Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance," Journal of Global Optimization, Springer, vol. 60(1), pages 103-120, September.
    7. Bozağaç, Doruk & Batmaz, İnci & Oğuztüzün, Halit, 2016. "Dynamic simulation metamodeling using MARS: A case of radar simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 124(C), pages 69-86.
    8. Reynes, Christelle & Sabatier, Robert & Molinari, Nicolas, 2006. "Choice of B-splines with free parameters in the flexible discriminant analysis context," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1765-1778, December.
    9. Francesco Campanella, 2014. "Assess the Rating of SMEs by using Classification And Regression Trees (CART) with Qualitative Variables," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 16-32, August.
    10. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    11. Akkoç, Soner, 2012. "An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish cred," European Journal of Operational Research, Elsevier, vol. 222(1), pages 168-178.
    12. Mostafa, Mohamed M. & Nataraajan, Rajan, 2009. "A neuro-computational intelligence analysis of the ecological footprint of nations," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3516-3531, July.
    13. Ayşe Özmen & Gerhard-Wilhelm Weber & Zehra Çavuşoğlu & Özlem Defterli, 2013. "The new robust conic GPLM method with an application to finance: prediction of credit default," Journal of Global Optimization, Springer, vol. 56(2), pages 233-249, June.
    14. Gerunov, Anton, 2016. "Modeling Economic Choice under Radical Uncertainty: Machine Learning Approaches," MPRA Paper 69199, University Library of Munich, Germany.
    15. repec:eee:tefoso:v:120:y:2017:i:c:p:184-194 is not listed on IDEAS
    16. repec:spr:fininn:v:1:y:2015:i:1:d:10.1186_s40854-015-0005-6 is not listed on IDEAS

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