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  Data mining problems and solutions for response modeling in CRM

Cho, S., Shin, H., Yu E, Ha, K., & MacLachlan, D. (2006). Data mining problems and solutions for response modeling in CRM. Entrue Journal of Information Technology, 5(1), 55-64.

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Cho, S, Author
Shin, H1, Author           
Yu E, Ha, K, Author
MacLachlan, D, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: We present three data mining problems that are often encountered in building a response model. They are robust modeling, variable selection and data selection. Respective algorithmic solutions are given. They are bagging based ensemble, genetic algorithm based wrapper approach and nearest neighbor-based data selection in that order. A real world data set from Direct Marketing Educational Foundation, or DMEF4, is used to show their effectiveness. Proposed methods were found to solve the problems in a practical way.

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 Dates: 2006-03
 Publication Status: Issued
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 Identifiers: BibTex Citekey: 3816
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Title: Entrue Journal of Information Technology
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 5 (1) Sequence Number: - Start / End Page: 55 - 64 Identifier: -