Return to search

arules - A Computational Environment for Mining Association Rules and Frequent Item Sets

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)

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3976
Date January 2005
CreatorsHornik, Kurt, Grün, Bettina, Hahsler, Michael
PublisherAmerican Statistical Association
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypeArticle, PeerReviewed
Formatapplication/pdf
Relationhttp://www.jstatsoft.org/v14/i15, http://epub.wu.ac.at/3976/

Page generated in 0.0016 seconds