|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.|
Page views:: 17763. Submitted: 2005-04-15. Published: 2005-09-29.
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets
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) or a GPL-compatible license.