International Journal of System and Software Engineering

1. K. V. N. K. Prasad – Department Of Statistics, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

2. G.v.s.r. Anjaneyulu – Department Of Statistics, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India.

Received
21-Sep-2017
Accepted
-
Published
21-Sep-2017
Abstract
This study focuses on how to support marketing decision makers better in identifying better prospective customers by using generalised additive models (GAMs). Compared to logistic regression, GAM relaxes the linearity constraint which allows for complex non-linear fits to the data. In this paper, we examine how GAM-based logistic models perform compared to traditional logistic regression model and also provide some implications.
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