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PaKDD-2007: A Near-Linear Model for the Cross-Selling Problem

PaKDD-2007: A Near-Linear Model for the Cross-Selling Problem

Thierry V. de Merckt, Jean-Francois Chevalier
Copyright: © 2008 |Volume: 4 |Issue: 2 |Pages: 9
ISSN: 1548-3924|EISSN: 1548-3932|ISSN: 1548-3924|EISBN13: 9781615202041|EISSN: 1548-3924|DOI: 10.4018/jdwm.2008040106
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MLA

de Merckt, Thierry V., and Jean-Francois Chevalier. "PaKDD-2007: A Near-Linear Model for the Cross-Selling Problem." IJDWM vol.4, no.2 2008: pp.46-54. http://doi.org/10.4018/jdwm.2008040106

APA

de Merckt, T. V. & Chevalier, J. (2008). PaKDD-2007: A Near-Linear Model for the Cross-Selling Problem. International Journal of Data Warehousing and Mining (IJDWM), 4(2), 46-54. http://doi.org/10.4018/jdwm.2008040106

Chicago

de Merckt, Thierry V., and Jean-Francois Chevalier. "PaKDD-2007: A Near-Linear Model for the Cross-Selling Problem," International Journal of Data Warehousing and Mining (IJDWM) 4, no.2: 46-54. http://doi.org/10.4018/jdwm.2008040106

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Abstract

This article presents VADIS Consulting’s solution for the cross-selling problem of the PAKDD_2007 competition. For this competition, we have used our in-house developed tool RANK, which automates a lot of important tasks that must be done to provide a good solution for predictive modeling projects. It was for us a way of benchmarking our 3 years of investment effort against other tools and techniques. RANK encodes some important steps of the CRISP-DM methodology: Data Quality Audit, Data Transformation, Modeling, and Evaluation. We have used RANK as we would do in a normal project, however with much less access to the business information, and hence the task was quite elementary: we have audited the data quality and found some problems that were further corrected. We have then let RANK build a model by applying its standard recoding, and then applied automatic statistical evaluation for variable selection and pruning. The result was not extremely good in terms of prediction, but the model was extremely stable, which is what we were looking for.

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