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Authors: Michael Hahsler, Bettina Grün, Kurt Hornik
Title: [download]
(14166)
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
Reference: Vol. 14, Issue 15, Sep 2005
Submitted 2005-04-15, Accepted 2005-09-29
Type: Article
Abstract:

Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases. The R package arules presented in this paper provides a basic infrastructure for creating and manipulating input data sets and for analyzing the resulting itemsets and rules. The package also includes interfaces to two fast mining algorithms, the popular C implementations of Apriori and Eclat by Christian Borgelt. These algorithms can be used to mine frequent itemsets, maximal frequent itemsets, closed frequent itemsets and association rules.

Paper: [download]
(14166)
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
(application/pdf, 404.2 KB)
Supplements: [download]
(1482)
arules_0.2-5.tar.gz: R source package
(application/x-gzip, 1.5 MB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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