Skip Content
You are currently on the new version of our website. Access the old version .
  • Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Association for Scientific Research (ASR).
  • Article
  • Open Access

1 December 2013

A Comparative Study of Artificial Neural Networks and Logistic Regression for Classification of Marketing Campaign Results

and
Department of Statistics, Hacettepe University, 06800, Beytepe, Ankara, Turkey
*
Authors to whom correspondence should be addressed.

Abstract

In this study, we focus on Artificial Neural Networks which are popularly used as universal non-linear inference models and Logistic Regression, which is a well known classification method in the field of statistical learning; there are many classification algorithms in the literature, though. We briefly introduce the techniques and discuss the advantages and disadvantages of these two methods through an application with real-world data set related with direct marketing campaigns of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit or not after campaigns.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.