Book Image

Practical Predictive Analytics

By : Ralph Winters
Book Image

Practical Predictive Analytics

By: Ralph Winters

Overview of this book

This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get started with a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio, and a description of the best practices for organizing your projects. On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement and successfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn why collaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model. We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

What is market basket analysis?


If you have survived the last chapter, you will now be introduced to the world of market basket analysis (MBA). Market basket analysis (also sometimes called affinity analysis), is a predictive analytics technique that is used heavily in the retail industry in order to identify baskets of items that are purchased together. The typical use case for this is the supermarket shopping cart in which a shopper would typically purchase an assortment of items such as milk, bread, cheese, and so on, and the algorithm will predict how purchasing certain items together will affect the purchase of other items. It is one of those methods that retailers use to know to start sending you coupons and emails for things that you didn't know you needed!

One often quoted example of MBA is the relationship between diapers and beer:

"One super market chain discovered in its analysis that customers that bought diapers often bought beer as well, have put the diapers close to beer coolers...