In part 1 we gave a brief introduction to logistic regression and indicated when it might be appropriate to use it in business analytics settings. Probably the best definition of Logistic regression is this " ... a mathematical modeling approach in which the best-fitting, yet least-restrictive model is desired to describe the relationship between several independent explanatory variables and a dependent dichotomous response variable".
In this previous article we described how to construct basic tools such as the "confusion matrix" and Lift/Gain charts for evaluating classification models used for business analytics and predictive analytics. In this article we describe another common evaluation tool - the Receiver Operating Characteristics (ROC) chart and its Area Under Curve (AUC).
The process of developing models for advanced business analytics deployment follows a process that is similar to this diagram.