R package arules: Mining Association Rules and Frequent Itemsets. Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides interfaces to C implementations of the association mining algorithms Apriori and Eclat by C. Borgelt.

References in zbMATH (referenced in 19 articles , 2 standard articles )

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  1. Page, Garritt L.; Quintana, Fernando A.; Rosner, Gary L.: Discovering interactions using covariate informed random partition models (2021)
  2. Fürnkranz, Johannes; Kliegr, Tomáš; Paulheim, Heiko: On cognitive preferences and the plausibility of rule-based models (2020)
  3. Modesto Escobar, Luis Martinez-Uribe: Network Coincidence Analysis: The netCoin R Package (2020) not zbMATH
  4. Szymon Maksymiuk, Alicja Gosiewska, Przemyslaw Biecek: Landscape of R packages for eXplainable Artificial Intelligence (2020) arXiv
  5. Ramasubramanian, Karthik; Singh, Abhishek: Machine learning using R. With time series and industry-based use cases in R (2019)
  6. Mihelčić, Matej; Šmuc, Tomislav: Targeted and contextual redescription set exploration (2018)
  7. Michael Scholz: R Package clickstream: Analyzing Clickstream Data with Markov Chains (2016) not zbMATH
  8. Ji, Zhanglong; Elkan, Charles: Differential privacy based on importance weighting (2013)
  9. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
  10. Ledolter, Johannes: Data mining and business analytics with R (2013)
  11. Zhao, Yanchang: R and data mining. Examples and case studies (2013)
  12. Blockeel, Hendrik; Calders, Toon; Fromont, Élisa; Goethals, Bart; Prado, Adriana: An inductive database system based on virtual mining views (2012)
  13. Kenett, Ron S.: ’The COM-Poisson model for count data: a survey of methods and applications’ by K. Sellers, S. Borle and G. Shmueli (2012)
  14. Hahsler, Michael; Chelluboina, Sudheer; Hornik, Kurt; Buchta, Christian: The arules R-package ecosystem: analyzing interesting patterns from large transaction data sets (2011)
  15. Williams, Graham: Data Mining with Rattle and R. The art of excavating data for knowledge discovery. (2011)
  16. Hornik, Kurt; Buchta, Christian; Zeileis, Achim: Open-source machine learning: R meets Weka (2009)
  17. Hahsler, Michael; Buchta, Christian; Hornik, Kurt: Selective association rule generator (2008)
  18. McNicholas, P. D.; Murphy, T. B.; O’Regan, M.: Standardising the lift of an association rule (2008)
  19. Michael Hahsler; Bettina Grün; Kurt Hornik: arules - A Computational Environment for Mining Association Rules and Frequent Item Sets (2005) not zbMATH