arules - A computational environment for mining association rules and frequent item sets

Michael Hahsler, Bettina Grün, Kurt Hornik

Publication: Scientific journalJournal articlepeer-review

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. (authors' abstract)
Original languageGerman (Austria)
Pages (from-to)1 - 25
JournalJournal of Statistical Software
Volume14
Issue number15
Publication statusPublished - 1 Nov 2005

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