Chapter 3. Predicting Sports Winners with Decision Trees

In this chapter, we will look at predicting the winner of sports matches using a different type of classification algorithm: decision trees. These algorithms have a number of advantages over other algorithms. One of the main advantages is that they are readable by humans. In this way, decision trees can be used to learn a procedure, which could then be given to a human to perform if needed. Another advantage is that they work with a variety of features, which we will see in this chapter.

We will cover the following topics in this chapter:

• Using the pandas library for loading and manipulating data
• Decision trees
• Random forests
• Using real-world datasets in data mining
• Creating new features and testing them in a robust framework

Loading the dataset

In this chapter, we will look at predicting the winner of games of the National Basketball Association (NBA). Matches in the NBA are often close and can be decided in the last minute, making...