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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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Chapter 2. Mining Frequent Patterns, Associations, and Correlations

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. ...

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