This workshop will introduce the basic concepts and procedures for predictive modeling in R including:
- How to evaluate the quality of predictive models using confusion matrices and ROC curves
- Classification and regression trees (CART methods)
- Ensemble methods (e.g. random forests, boosting, bagging)
- Discussion of issues and limitations of “black box” predictive modeling