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Solving and interpreting binary classification problems in marketing with SVMs

Author

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  • Bioch, J.C.
  • Groenen, P.J.F.
  • Nalbantov, G.I.

Abstract

Marketing problems often involve inary classification of customers into ``buyers'' versus ``non-buyers'' or ``prefers brand A'' versus ``prefers brand B''. These cases require binary classification models such as logistic regression, linear, and quadratic discriminant analysis. A promising recent technique for the binary classification problem is the Support Vector Machine (Vapnik (1995)), which has achieved outstanding results in areas ranging from Bioinformatics to Finance. In this paper, we compare the performance of the Support Vector Machine against standard binary classification techniques on a marketing data set and elaborate on the interpretation of the obtained results.

Suggested Citation

  • Bioch, J.C. & Groenen, P.J.F. & Nalbantov, G.I., 2005. "Solving and interpreting binary classification problems in marketing with SVMs," Econometric Institute Research Papers EI 2005-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:7038
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    References listed on IDEAS

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    1. Makoto Abe, 1995. "A Nonparametric Density Estimation Method for Brand Choice Using Scanner Data," Marketing Science, INFORMS, vol. 14(3), pages 300-325.
    2. Patricia M. West & Patrick L. Brockett & Linda L. Golden, 1997. "A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice," Marketing Science, INFORMS, vol. 16(4), pages 370-391.
    3. Franses,Philip Hans & Paap,Richard, 2010. "Quantitative Models in Marketing Research," Cambridge Books, Cambridge University Press, number 9780521143653.
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    1. Andrey Zahariev & Mikhail Zveryаkov & Stoyan Prodanov & Galina Zaharieva & Petko Angelov & Silvia Zarkova & Mariana Petrova, 2020. "Debt management evaluation through Support Vector Machines: on the example of Italy and Greece," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(3), pages 2382-2393, March.

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