Uplift Regression: The R Package tools4uplift

Abstract

Uplift modeling aims at predicting the causal effect of an action such as a medical treatment or a marketing campaign on a particular individual, by taking into consideration the response to a treatment. The treatment group contains individuals who are subject to an action; a control group serves for comparison. Uplift modeling is used to order the individuals with respect to the value of a causal effect, e.g., positive, neutral, or negative. Though there are some computational methods available for uplift modeling, most of them exclude statistical regression models. The R Package tools4uplift intends to fill this gap. This package comprises tools for: i) quantization, ii) visualization, iii) feature selection, iv) parameter estimation and v) model validation.