RWeka

Open-source machine learning: R meets Weka. The Waikato Environment for Knowleage Analysis (Weka) is an open-source project in machine learning covering classification, regression, clustering, association rules and visualization. It is implemented on Java and released under GPL. This paper is devoted to the Weka interface for R-software provided by the R extension package RWeka. The interfacing methodology, limitations and possible extensions are discussed.


References in zbMATH (referenced in 17 articles , 1 standard article )

Showing results 1 to 17 of 17.
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  1. Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan: SIRUS: stable and interpretable RUle set for classification (2021)
  2. F. Aragón-Royón, A. Jiménez-Vílchez, A. Arauzo-Azofra, J. M. Benítez: FSinR: an exhaustive package for feature selection (2020) arXiv
  3. Ferri, Cèsar; Hernández-Orallo, José; Flach, Peter: Setting decision thresholds when operating conditions are uncertain (2019)
  4. Gilles Kratzer, Fraser Iain Lewis, Arianna Comin, Marta Pittavino, Reinhard Furrer: Additive Bayesian Network Modelling with the R Package abn (2019) arXiv
  5. Reto Bürgin; Gilbert Ritschard: Coefficient-Wise Tree-Based Varying Coefficient Regression with vcrpart (2017) not zbMATH
  6. Azam, Muhammad; Aslam, Muhammad; Pfeiffer, Karl Peter: Three steps strategy to search for optimum classification trees (2016)
  7. Hernández-Orallo, José; Ferri, Cèsar; Lachiche, Nicolas; Martínez-Usó, Adolfo; Ramírez-Quintana, M. José: Binarised regression tasks: methods and evaluation metrics (2016)
  8. Hothorn, Torsten: partykit: a modular toolkit for recursive partytioning in \textttR (2015)
  9. Henelius, Andreas; Puolamäki, Kai; Boström, Henrik; Asker, Lars; Papapetrou, Panagiotis: A peek into the black box: exploring classifiers by randomization (2014) ioport
  10. Thomas Grubinger; Achim Zeileis; Karl-Peter Pfeiffer: evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R (2014) not zbMATH
  11. Kuhn, Max; Johnson, Kjell: Applied predictive modeling (2013)
  12. Mehmood, Rashid; Riaz, Muhammad; Does, Ronald J. M. M.: Efficient power computation for (r) out of (m) runs rules schemes (2013)
  13. Rusch, Thomas; Zeileis, Achim: Gaining insight with recursive partitioning of generalized linear models (2013)
  14. Brogini, Adriana; Slanzi, Debora: On using Bayesian networks for complexity reduction in decision trees (2010)
  15. Hornik, Kurt; Buchta, Christian; Zeileis, Achim: Open-source machine learning: R meets Weka (2009)
  16. Urbanek, Simon: How to talk to strangers: ways to leverage connectivity between R, Java and Objective C (2009)
  17. Ingo Feinerer; Kurt Hornik; David Meyer: Text Mining Infrastructure in R (2008) not zbMATH