Chapter 12: Regression

In the previous chapter, we studied classification – one of the two supervised learning techniques available in the Elastic Stack. However, not all real-world applications of supervised learning lend themselves to the format required for classification. What if, for example, we wanted to predict the sales prices of apartments in our neighborhood? Or the amount of money a customer will spend in our online store? Notice that the value we are interested in here is not a discrete class, but instead is a value that can take a variety of continuous values in a range.

This is exactly the problem solved by regression analysis. Instead of predicting which class a given datapoint belongs to, we can predict a continuous value. Although the end goal is slightly different than that in classification, the underlying algorithm that is used for regression is the same as the one we examined for classification in the previous chapter. Thus, we already know a lot about...