References in zbMATH (referenced in 162 articles )

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  1. Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan: SIRUS: stable and interpretable RUle set for classification (2021)
  2. Ertefaie, Ashkan; McKay, James R.; Oslin, David; Strawderman, Robert L.: Robust Q-learning (2021)
  3. Kolosova, Tanya; Berestizhevsky, Samuel: Supervised machine learning. Optimization framework and applications with SAS and R (2021)
  4. Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani: Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties (2020) arXiv
  5. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  6. Calhoun, Peter; Hallett, Melodie J.; Su, Xiaogang; Cafri, Guy; Levine, Richard A.; Fan, Juanjuan: Random forest with acceptance-rejection trees (2020)
  7. Calissano, Anna; Vantini, Simone; Arena, Marika: Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform (2020)
  8. Elman, Miriam R.; Minnier, Jessica; Chang, Xiaohui; Choi, Dongseok: Noise accumulation in high dimensional classification and total signal index (2020)
  9. Ertefaie, Ashkan; Johnson, Brent A.: Comment: Outcome-wide individualized treatment strategies (2020)
  10. Genuer, Robin; Poggi, Jean-Michel: Random forests with R (2020)
  11. Lopes, Miles E.: Estimating a sharp convergence bound for randomized ensembles (2020)
  12. Lu, Haihao; Mazumder, Rahul: Randomized gradient boosting machine (2020)
  13. Mišić, Velibor V.: Optimization of tree ensembles (2020)
  14. Pan, Yuqing; Mai, Qing: Efficient computation for differential network analysis with applications to quadratic discriminant analysis (2020)
  15. Roustant, Olivier; Padonou, Espéran; Deville, Yves; Clément, Aloïs; Perrin, Guillaume; Giorla, Jean; Wynn, Henry: Group kernels for Gaussian process metamodels with categorical inputs (2020)
  16. Sage, Andrew J.; Genschel, Ulrike; Nettleton, Dan: Tree aggregation for random forest class probability estimation (2020)
  17. Ahonen, Ilmari; Nevalainen, Jaakko; Larocque, Denis: Prediction with a flexible finite mixture-of-regressions (2019)
  18. Azmi, Mohamed; Runger, George C.; Berrado, Abdelaziz: Interpretable regularized class association rules algorithm for classification in a categorical data space (2019)
  19. Badih, Ghattas; Pierre, Michel; Laurent, Boyer: Assessing variable importance in clustering: a new method based on unsupervised binary decision trees (2019)
  20. Casalicchio, Giuseppe; Bossek, Jakob; Lang, Michel; Kirchhoff, Dominik; Kerschke, Pascal; Hofner, Benjamin; Seibold, Heidi; Vanschoren, Joaquin; Bischl, Bernd: \textttOpenML: an \textttRpackage to connect to the machine learning platform openml (2019)

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