Open-source machine learning: R meets Weka
By Kurt Hornik, Christian Buchta, Achim Zeileis. Computational statistics (Zeitschrift), 2009
399 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/e7d4989aeb3aba1bca30035fc1da28a518f9de39
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Houtao Deng
- Kai Puolamäki
- Andreas Henelius
- Achim Zeileis
- Thomas Rusch
- Torsten Hothorn
- Tong Wang
- M. Buehlmaier
In Information Systems
- Houtao Deng
- Kai Puolamäki
- Andreas Henelius
- M. Buehlmaier
- Tong Wang
- Torsten Hothorn
- Thomas Rusch
- Elaine Tavares
Citations in the corpus
- A peek into the black box: exploring classifiers by randomization (2014, methodology): “Of the classifiers, 14 were from the Weka data mining software (Hall et al. 2009), used via RWeka (Hornik et al. 2009).”
- Partykit: a modular toolkit for recursive partytioning in R (2015, methodology): “Specifically, tree objects learned by rpart (Therneau and Atkinson, 1997, implementing CART, Breiman et al., 1984) and by J48 from RWeka (Hornik et al., 2009, interfacing Weka's J4.”
- Multi-Value Rule Sets (2017, methodology): “We use R and python packages for random forest, SBRL, CBA and Ripper [4] and use the publicly available code for BRS. Due to the computation limit, SBRL cannot handle rules longer than 3 for these datasets, so we set the maximum rule length to 2.”
- Gaining insight with recursive partitioning of generalized linear models (2013, methodology): “We fit LMT with Weka (Hall et al. 2009) for which we employ the RWeka interface (Hornik, Buchta, and Zeileis 2009).”
- CBC: An associative classifier with a small number of rules (2014, methodology): “We used the statistical programming language R [13] and R packages " RWeka " [11] and " arules " [9] to implement the algorithms considered in our experiments.”
- Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study (2017, methodology): “Results were obtained with the use of R statistical software (R Core Team 2016), and R additional packages (Feinerer et al. 2008; Bouchet-Valat 2014; Wickham 2009; Fellows 2014; Hornik et al. 2009; Csardi and Nepusz 2006).”
- The Role of the Media in Takeovers: Theory and Evidence (2015, positive): “The software implementation uses the R packages described in Feinerer et al. (2008) and Hornik et al. (2009).”