s like maximum depth of one, two or
three, though in kaggle people are doing like 8 to 10 or
something. But typically, the depth is much, much smaller
than for random forests. This means the model will be small
in memory, and also will be faster to predict since you have
less deep trees to traverse.
Before we go into implementation I want to talk a little bit
about analyzing the models. So again, because it’s a
tree-based model, the prediction is a linear combination of
trees, you can look at feature impo