This tutorial will provide an overview of using R to create effective predictive models in cases where at least one class has a low event frequency. These types of problems are often found in applications such as: click through rate prediction, disease prediction, chemical quantitative structure - activity modeling, network intrusion detection, and quantitative marketing. The session will step through the process of building, optimizing, testing, and comparing models that are focused on prediction. A case study is used to illustrate functionality.
