Regression analysis allows us to mathematically model the relationship between two variables using simple algebra. In this chapter, we will focus on covering another supervised learning technique: regression analysis or regression-based learning. In the previous chapter, we covered the basics of statistics that will be of use in this chapter. We will start with understanding how multiple variables can influence the outcome, and how statistical adjustment techniques can be used to arbitrate this influence, understand correlation and regression analysis using real world examples, and take a deep dive into concepts such as confounding and effect modification.
You will learn the basic and advanced concepts of this technique and get hands-on implementation guidance in simple, multiple linear regression, polynomial regression and logistic regression using Apache Mahout, R, Julia, Apache Spark, and Python.
At the end of this chapter, readers will have understood...