Introduction to arules – A computational environment for mining association rules and frequent item sets

  • Hahsler M
  • Grün B
  • Hornik K
  • 336


    Mendeley users who have this article in their library.
  • 115


    Citations of this article.


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.

Author-supplied keywords

  • apriori
  • association rules
  • data mining
  • eclat

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Michael Hahsler

  • Bettina Grün

  • Kurt Hornik

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free