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Mastering Machine Learning with R

You're reading from   Mastering Machine Learning with R Advanced machine learning techniques for building smart applications with R 3.5

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Product type Paperback
Published in Jan 2019
Publisher
ISBN-13 9781789618006
Length 354 pages
Edition 3rd Edition
Languages
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Author (1):
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Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
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Table of Contents (16) Chapters Close

Preface 1. Preparing and Understanding Data 2. Linear Regression FREE CHAPTER 3. Logistic Regression 4. Advanced Feature Selection in Linear Models 5. K-Nearest Neighbors and Support Vector Machines 6. Tree-Based Classification 7. Neural Networks and Deep Learning 8. Creating Ensembles and Multiclass Methods 9. Cluster Analysis 10. Principal Component Analysis 11. Association Analysis 12. Time Series and Causality 13. Text Mining 14. Creating a Package 15. Other Books You May Enjoy

Data understanding

For our business case, we'll focus on identifying the association rules for a grocery store. The dataset will be from the arules package and is called Groceries. This dataset consists of actual transactions over 30 days from a real-world grocery store and consists of 9,835 different purchases. All of the items purchased are put into one of 169 categories, for example, bread, wine, meat, and so on.

Let's say that we want to develop an understanding of what potential customers will purchase along with beer to identify the right product placement within the store or support a cross-selling campaign.

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