Tutorial: Predictive Modeling with R and the caret Package

Max Kuhn, Pfizer Global R&D, USA.


This course will provide an overview of using R for supervised learning (aka machine learning, pattern recognition, predictive analytics, etc). The session will step through the process of building, visualizing, testing and comparing models that are focused on prediction. The goal of the course is to provide a thorough workflow in R that can be used with many different modeling techniques. A case study is used to illustrate functionality.


Topics will include:

The length of the tutorial is not conducive to hands-on exercises, so laptops are not required. However, the illustrative data sets and code will be available online if participants would like to follow along.
Please check here for up to date tutorial resources.


Basic understanding of R (matrices, data frames, functions, etc) is needed. Some basic understanding of regression techniques is helpful.