We're going to explore the use of the mlr package, which stand for machine learning in R. The package supports multiple classes and ensemble methods. If you're familiar with sci-kit learn for Python, we could say that mlr endeavors to provide the same functionality for R. I intend to demonstrate how to use the package on a multiclass problem, then conclude by showing how to do an ensemble on the same data, so we can compare performances.

For the multiclass problem, we'll look at how to tune a random forest and then examine how to build an ensemble using random forest in conjunction with MARS, stacking those models by calling the generalized linear model function from the glmnet package.