Machine Learning Algorithms - Second Edition

Decision Trees and Ensemble Learning

In this chapter, we're going to discuss Binary Decision Trees and ensemble methods. Even though they're probably not the most common methods for classification, they offer a good level of simplicity and can be adopted for many tasks that don't require a high level of complexity. They're also quite useful when it's necessary to show how a decision process works because they are based on a structure that can be easily shown in presentations and described step by step.

Ensemble methods are a powerful alternative to complex algorithms because they try to exploit the statistical concept of a majority vote. Many weak learners can be trained to capture different elements and make their own predictions, which ...