ABSTRACT
Logistic regression is a popular technique for classifying individuals into two mutually exclusive and exhaustive categories, for example: buy-not buy or responder-nonresponder. It is the workhorse of response modeling as its results are considered the gold standard. Moreover, it is used as the benchmark for assessing the superiority of newer
techniques, such as GenIQ, a genetic model, and older techniques, such as CHAID, which is a regression tree. In database marketing, response to a prior solicitation is the binary class variable (defined by responder and nonresponder), and the logistic regression model is built to classify an individual as either most likely or least likely to respond to a future solicitation.
