|Authors:||Michael Hahsler, Bettina Grün, Kurt Hornik|
|Title:||arules - A Computational Environment for Mining Association Rules and Frequent Item Sets|
|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.|
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arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
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