Summary: Decision Trees and Random Forests

In this chapter, we’ve learned how to use decision trees and the ensemble models called random forests that are made up of many decision trees. Using these simply conceived models, we were able to make better predictions than we could with logistic regression, judging by the cross-validation ROC AUC score. This is often the case for many real-world problems.