Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Overview of this book

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more. You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.
Table of Contents (23 chapters)
Title Page
Credits
About the Author
About the Reviewers
Packt Upsell
Customer Feedback
Preface
16
Sources

An overview of a market basket analysis


Market basket analysis is a data mining technique that has the purpose of finding the optimal combination of products or services and allows marketers to exploit this knowledge to provide recommendations, optimize product placement, or develop marketing programs that take advantage of cross-selling. In short, the idea is to identify which items go well together, and profit from it.

You can think of the results of the analysis as an if...then statement. If a customer buys an airplane ticket, then there is a 46 percent probability that they will buy a hotel room, and if they go on to buy a hotel room, then there is a 33 percent probability that they will rent a car. 

However, it is not just for sales and marketing. It is also being used in fraud detection and healthcare; for example, if a patient undergoes treatment A, then there is a 26 percent probability that they might exhibit symptom X. Before going into the details, we should have a look at some...