In this chapter, we will focus on the utilization of some Apache Spark machine learning libraries, especially MLlib, as applied to a churn predictive modeling project.
Specifically, in this chapter, we will first review machine learning methods and the related computing for a churn prediction project, and will then discuss how Apache Spark MLlib makes things easy and fast. At the same time, with a real life churn prediction example, we will illustrate the step-by-step process of predicting churns with big data. The following topics will be covered in this chapter:
Spark for churn prediction
Methods for churn prediction
Feature preparation
Model estimation
Model evaluation
Results explanation
Model deployment