XGBoost Ensemble

This animation visualizes how XBoost builds an ensemble by sequentially adding four decision trees, each correcting the errors of the previous one. It demonstrates this process by showing the classification boundary improving to eliminate all mistakes on the left, while the loss metric drops from high to low on the right.