Maximum Features

We are getting close to the end of this chapter. You have already learned how to tune several of the most important hyperparameters for RandomForest. In this section, we will present you with another extremely important one: max_features.

Earlier, we learned that RandomForest builds multiple trees and takes the average to make predictions. This is why it is called a forest, but we haven't really discussed the "random" part yet. Going through this chapter, you may have asked yourself: how does building multiple trees help to get better predictions, and won't all the trees look the same given that the input data is the same?

Before answering these questions, let's use the analogy of a court trial. In some countries, the final decision of a trial is either made by a judge or a jury. A judge is a person who knows the law in detail and can decide whether a person has broken the law or not. On the other hand, a jury is composed of people from...