Consider the following algorithm for boosting a regression tree :

Consider the following algorithm for
boosting a regression tree:


Resource 1. Consider the following algorithm for boosting a regression tree: 0. Set and for all in the training set. 0. For b = 1, 2, …, B, repeat: 1. Fit a tree with d splits (d + 1 terminal nodes) to the training data (X, r) 1. Update by adding a shrunken version of the new tree: 1. Update the residuals 0. Output the boosted model: . Provide a formal explanation to why boosting using depth-one trees leads to an additive model of the form ? © 2021. Grand Canyon University. All Rights Reserved.