Chapter 5
Decision Trees and Random Forests
Section 2
Decision Trees
Decision trees and the machine learning models that are based on them, random forests and gradient boosted trees, are fundamentally different types of models than generalized linear models, such as logistic regression. GLMs are rooted in the theories of classical statistics, which have a long history. The mathematics behind linear regression were originally developed at the beginning of the 19th century, by Legendre and Gauss. Because of this, the normal distribution is also called the Gaussian. Here are the topics that we will cover now: