arules - A computational environment for mining association rules and frequent item sets

Michael Hahsler, Bettina Grün, Kurt Hornik

Publikation: Wissenschaftliche FachzeitschriftOriginalbeitrag in FachzeitschriftBegutachtung

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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. (authors' abstract)
OriginalspracheEnglisch
Seiten (von - bis)1 - 25
FachzeitschriftJournal of Statistical Software
Jahrgang14
Ausgabenummer15
DOIs
PublikationsstatusVeröffentlicht - 2005

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Österreichische Systematik der Wissenschaftszweige (ÖFOS)

  • 102022 Softwareentwicklung
  • 101029 Mathematische Statistik
  • 101018 Statistik

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