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Data Mining and Predictive Analytics, 2nd Edition
book

Data Mining and Predictive Analytics, 2nd Edition

by Chantal D. Larose, Daniel T. Larose
March 2015
Beginner to intermediate
824 pages
22h 57m
English
Wiley
Content preview from Data Mining and Predictive Analytics, 2nd Edition

Chapter 23Association Rules

23.1 Affinity Analysis and Market Basket Analysis

Affinity analysis is the study of attributes or characteristics that “go together.” Methods for affinity analysis, also known as market basket analysis, seek to uncover associations among these attributes; that is, it seeks to uncover rules for quantifying the relationship between two or more attributes. Association rules take the form “If antecedent, then consequent,” along with a measure of the support and confidence associated with the rule. For example, a particular supermarket may find that of the 1000 customers shopping on a Thursday night, 200 bought diapers, and of the 200 who bought diapers, 50 bought beer. Thus, the association rule would be: “If buy diapers, then buy beer,” with a support of c23-math-0001 and a confidence of c23-math-0002.

Examples of association tasks in business and research include

  • investigating the proportion of subscribers to your company's cell phone plan that respond positively to an offer of a service upgrade;
  • examining the proportion of children whose parents read to them who are themselves good readers;
  • predicting degradation in telecommunications networks;
  • finding out which items in a supermarket are purchased together, and which items are never purchased together;
  • determining the proportion ...
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ISBN: 9781118868706Purchase book