A COMPARATIVE STUDY OF ARTIFICIAL NEURAL NETWORKS AND LOGISTIC REGRESSION FOR CLASSIFICATION OF MARKETING CAMPAIGN RESULTS

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.