References in zbMATH (referenced in 79 articles )

Showing results 1 to 20 of 79.
Sorted by year (citations)

1 2 3 4 next

  1. Eun-Kyung Lee: PPtreeViz: An R Package for Visualizing Projection Pursuit Classification Trees (2018)
  2. Muñoz, Mario A.; Villanova, Laura; Baatar, Davaatseren; Smith-Miles, Kate: Instance spaces for machine learning classification (2018)
  3. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
  4. Bertsimas, Dimitris; Dunn, Jack: Optimal classification trees (2017)
  5. Conversano, Claudio; Dusseldorp, Elise: Modeling threshold interaction effects through the logistic classification trunk (2017)
  6. Deprez, Philippe; Shevchenko, Pavel V.; Wüthrich, Mario V.: Machine learning techniques for mortality modeling (2017)
  7. Ghesmoune, Mohammed; Azzag, Hanene; Benbernou, Salima; Lebbah, Mustapha; Duong, Tarn; Ouziri, Mourad: Big Data: from collection to visualization (2017)
  8. Hajjem, Ahlem; Larocque, Denis; Bellavance, François: Generalized mixed effects regression trees (2017)
  9. He Zhao and Graham Williams and Joshua Huang: wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests (2017)
  10. Marjolein Fokkema: pre: An R Package for Fitting Prediction Rule Ensembles (2017) arXiv
  11. Ott, Armin; Hapfelmeier, Alexander: Nonparametric subgroup identification by PRIM and CART: a simulation and application study (2017)
  12. Azam, Muhammad; Aslam, Muhammad; Pfeiffer, Karl Peter: Three steps strategy to search for optimum classification trees (2016)
  13. Beata Nowok and Gillian Raab and Chris Dibben: synthpop: Bespoke Creation of Synthetic Data in R (2016)
  14. Bischl, Bernd; Kerschke, Pascal; Kotthoff, Lars; Lindauer, Marius; Malitsky, Yuri; Fréchette, Alexandre; Hoos, Holger; Hutter, Frank; Leyton-Brown, Kevin; Tierney, Kevin; Vanschoren, Joaquin: ASlib: a benchmark library for algorithm selection (2016)
  15. Bischl, Bernd; Kühn, Tobias; Szepannek, Gero: On class imbalance correction for classification algorithms in credit scoring (2016)
  16. Dinwoodie, Ian H.: Computational methods for asynchronous basins (2016)
  17. Tutz, Gerhard; Schmid, Matthias: Modeling discrete time-to-event data (2016)
  18. Ustun, Berk; Rudin, Cynthia: Supersparse linear integer models for optimized medical scoring systems (2016)
  19. Bernd Bischl; Michel Lang; Olaf Mersmann; Jörg Rahnenführer; Claus Weihs: BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments (2015)
  20. Cichosz, Paweł: Data mining algorithms. Explained using R (2015)

1 2 3 4 next