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.
Year of publication: |
2005-09-29
|
---|---|
Authors: | Hahsler, Michael ; GrĂ¼n, Bettina ; Hornik, Kurt |
Published in: |
Journal of Statistical Software. - American Statistical Association. - Vol. 14.2005, i15
|
Publisher: |
American Statistical Association |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Warenkorbanalyse mit Hilfe der Statistik-Software R
Hahsler, Michael, (2006)
-
Data Mining und Marketing am Beispiel der explorativen Warenkorbanalyse
Reutterer, Thomas, (2007)
-
Abhandlungen - Data Mining und Marketing am Beispiel der explorativen Warenkorbanalyse.
Reutterer, Thomas, (2007)
- More ...