R for Data Science Cookbook

Chapter 9. Rule and Pattern Mining with R

This chapter covers the following topics:

• Transforming data into transactions
• Displaying transactions and associations
• Mining associations with the Apriori rule
• Pruning redundant rules
• Visualizing association rules
• Mining frequent itemsets with Eclat
• Creating transactions with temporal information
• Mining frequent sequential patterns with cSPADE

Introduction

The majority of readers will be familiar with Wal-Mart moving beer next to diapers in its stores because it found that the purchase of both products is highly correlated. This is one example of what data mining is about; it can help us find how items are associated in a transaction dataset. Using this skill, a business can explore the relationship between items, ...