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)
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3976 |
| Date | January 2005 |
| Creators | Hornik, Kurt, Grün, Bettina, Hahsler, Michael |
| Publisher | American Statistical Association |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Relation | http://www.jstatsoft.org/v14/i15, http://epub.wu.ac.at/3976/ |
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