I am having a little trouble understanding the difference between what a "Node" of a tree and a "Leaf" of a tree.
Suppose I am trying to decide the size of coffee a person may like. There are three categories: small, medium, and large based off the peoples age, height, weight, income.
So I have four predictors and 3 possible outcomes. When looking at many gradient boosting algorithms, there are parameters that can increase the number of leaves.
My understanding of this (correct me if wrong), but I will illustrate with a picture. Assuming each yes/no split is 50/50
Does increasing the number of leaves to lets say 3 leaves change it from yes/no aka 50/50 to 33/33/33? This is a little confusing to me. Thank you for any clarification.