Data Science Projects with Python - Second Edition

5. Decision Trees and Random Forests

Overview

In this chapter, we'll shift our focus to another type of machine learning model that has taken data science by storm in recent years: tree-based models. In this chapter, after learning about trees individually, you'll then learn how models made up of many trees, called random forests, can improve the overfitting associated with individual trees. After reading this chapter, you will be able to train decision trees for machine learning purposes, visualize trained decision trees, and train random forests and visualize the results.

Introduction

In the last two chapters, we have gained a thorough understanding of the workings of logistic regression. We have also gotten a lot of experience with ...