This example uses the Covertype dataset from the UCI Machine Learning Repository. The task is to predict forest cover type from cartographic variables. The dataset includes 506,011 instances with 12 input features: 10 numerical features and 2 categorical features. Each instance is categorized into 1 of 7 classes.