Data Science for Marketing Analytics

Chapter 9

Modeling Customer Choice

Learning Objectives

By the end of this chapter, you will be able to:

• Describe the logic behind multiclass classification problems
• Create a multiclass classification classifier
• Use different sampling techniques to solve the problem of imbalanced data

This chapter covers different types of multiclass classification problems and explains how to calculate performance metrics and deal with imbalanced data.

Introduction

In the previous chapters, you learned about common classification algorithms such as logistic regression, SVM, decision tree, and random forest. You also learned the advantages and disadvantages of each of these algorithms. You implemented these algorithms using the most popular machine learning ...