Resource title

A computational environment for mining association rules and frequent item sets

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Resource description

Mining frequent itemsets and association rules is a popular and well researched approach to 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. (author's abstract) ; Series: Research Report Series / Department of Statistics and Mathematics

Resource author

Michael Hahsler, Bettina GrĂ¼n, Kurt Hornik

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Resource language

en

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application/pdf

Resource resource URL

http://epub.wu.ac.at/132/1/document.pdf

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