In this section, we'll see how to use DTs to solve both regression and classification problems. In the previous two chapters, Chapter 2, Scala for Regression Analysis, and Chapter 3, Scala for Learning Classification, we solved customer churn and insurance-severity claim problems. Those were classification and regression problems, respectively. In both approaches, we used other classic models. However, we'll see how we can solve them with tree-based and ensemble techniques. We'll use the DT implementation from the Apache Spark ML package in Scala.
Decision trees for supervised learning
Decision trees for classification
First of all, we know the customer churn prediction problem in Chapter 3, Scala for Learning...
