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 \pkgarules 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.
CITATION STYLE
Hahsler, M., Grün, B., Hornik, K., & Buchta, C. (2008). Mathematical Tools for Data Mining. Journal of Statistical Software, 14(15), 1–25. Retrieved from http://www.jstatsoft.org/counter.php?id=140&url=v14/i15&ct=2; http://www.jstatsoft.org/counter.php?id=140&url=v14/i15/v14i15.pdf&ct=1%5Cnhttp://link.springer.com/10.1007/978-1-84800-201-2
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