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Algorithms for Association Rules

Hegland, Markus

Description

Association rules are "if-then rules" with two measures which quantify the support and confidence of the rule for a given data set. Having their origin in market basked analysis, association rules are now one of the most popular tools in data mining. This popularity is to a large part due to the availability of efficient algorithms following from the development of the Apriori algorithm. We will review the basic Apriori algorithm and discuss variants for distributed data, inclusion of...[Show more]

CollectionsANU Research Publications
Date published: 2003
Type: Book chapter
URI: http://hdl.handle.net/1885/77129

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