XGBoost in R: A Step-by-Step Example

Boosting is a technique in machine learning that has been shown to produce models with high predictive accuracy. One of the most common ways to implement boosting in practice is to use XGBoost, short for "extreme gradient boosting." This tutorial provides a step-by-step example of how to use XGBoost to fit a boosted model in R. For this example we'll fit a boosted regression model to the Boston dataset from the MASS package. This dataset contains 13 predictor variables that we'll use to predict one response variable called mdev, which represents the median value of homes in different census tracts around Boston. We can see that the dataset contains 506 observations and 14 total variables.