In this chapter, we will learn how to mine frequent patterns, association rules, and correlation rules when working with R programs. Then, we will evaluate all these methods with benchmark data to determine the interestingness of the frequent patterns and rules. We will cover the following topics in this chapter:
Introduction to associations and patterns
Market basket analysis
Hybrid association rules mining
Mining sequence datasets
High-performance algorithms
The algorithms to find frequent items from various data types can be applied to numeric or categorical data. Most of these algorithms have one common basic algorithmic form, which is A-Priori, depending on certain circumstances. Another basic algorithm is FP-Growth, which is similar to A-Priori. Most pattern-related mining algorithms derive from these basic algorithms.
With frequent patterns found as one input, many algorithms are designed to find association and correlation...