How it works...

We begin by reading in our data (step 1). We then create a train-test split (step 2). We proceed to instantiate an XGBoost classifier with default parameters and fit it to our training set (step 3). Finally, in step 4, we use our XGBoost classifier to predict on the testing set. We then produce the measured accuracy of our XGBoost model's predictions.