Introduction to Statistical and Machine Learning Methods for Data Science

Chapter 5: Advanced Topics in Supervised Models

Chapter Overview

In this chapter, you will learn about advanced topics in machine learning and supervised learning modeling. This chapter focuses on nontraditional machine learning models like support vector machines and factorization machines, as well as advanced methods for supervised modeling, such as ensemble models and two-stage models.

Support vector machines are a very efficient classifier, allowing data scientists to fit a model regardless of the functional form, or the relationship between the input variables and the target. Factorization machines are a common model for recommendation systems, allowing data scientists to predict, for example, customer ratings for items.

The main goals of ...