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Classification Of 3G Mobile Phone Customers
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Author(s): Ankur Jain (Inductis India Pvt. Ltd., India), Lalit Wangikar (Inductis India Pvt. Ltd., India), Martin Ahrens (Inductis India Pvt. Ltd., India), Ranjan Rao (Inductis India Pvt. Ltd., India), Suddha Sattwa Kundu (Inductis India Pvt. Ltd., India)and Sutirtha Ghosh (Inductis India Pvt. Ltd., India)
Copyright: 2008
Pages: 8
Source title:
Electronic Commerce: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Annie Becker (Florida Institute of Technology, USA)
DOI: 10.4018/978-1-59904-943-4.ch172
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Abstract
In this article we discuss how we have predicted the third generation (3G) customers using lo-gistic regression analysis and statistical tools like Classification and Regression Tree (CART), Multivariate Adaptive Regression Splines (MARS), and other variables derived from the raw variables. The basic idea reflected in this paper is that the performance of logistic regression using raw variables standalone can be improved upon, by the use for various functions of the raw variables and dummies representing potential segments of the population.
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