References in zbMATH (referenced in 167 articles )

Showing results 1 to 20 of 167.
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  1. Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan: SIRUS: stable and interpretable RUle set for classification (2021)
  2. Bertsimas, Dimitris; Dunn, Jack; Wang, Yuchen: Near-optimal nonlinear regression trees (2021)
  3. Ducas, Léo; Yu, Yang: Learning strikes again: the case of the DRS signature scheme (2021)
  4. Ertefaie, Ashkan; McKay, James R.; Oslin, David; Strawderman, Robert L.: Robust Q-learning (2021)
  5. Javadi, Sara; Bahrampour, Abbas; Saber, Mohammad Mehdi; Garrusi, Behshid; Baneshi, Mohammad Reza: Evaluation of four multiple imputation methods for handling missing binary outcome data in the presence of an interaction between a dummy and a continuous variable (2021)
  6. Kolosova, Tanya; Berestizhevsky, Samuel: Supervised machine learning. Optimization framework and applications with SAS and R (2021)
  7. Minucci, Sarah; Heise, Rebecca L.; Valentine, Michael S.; Kamga Gninzeko, Franck J.; Reynolds, Angela M.: Mathematical modeling of ventilator-induced lung inflammation (2021)
  8. Olivia M. Bernstein, Brian G. Vegetabile, Christian R. Salazar, Joshua D. Grill, Daniel L. Gillen: Adjustment for Biased Sampling Using NHANES Derived Propensity Weights (2021) arXiv
  9. Begüm D. Topçuoğlu; Zena Lapp; Kelly L. Sovacool; Evan Snitkin; Jenna Wiens; Patrick D. Schloss: mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines (2020) not zbMATH
  10. Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani: Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties (2020) arXiv
  11. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  12. Calhoun, Peter; Hallett, Melodie J.; Su, Xiaogang; Cafri, Guy; Levine, Richard A.; Fan, Juanjuan: Random forest with acceptance-rejection trees (2020)
  13. Calissano, Anna; Vantini, Simone; Arena, Marika: Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform (2020)
  14. Elman, Miriam R.; Minnier, Jessica; Chang, Xiaohui; Choi, Dongseok: Noise accumulation in high dimensional classification and total signal index (2020)
  15. Ertefaie, Ashkan; Johnson, Brent A.: Comment: Outcome-wide individualized treatment strategies (2020)
  16. Genuer, Robin; Poggi, Jean-Michel: Random forests with R (2020)
  17. Kandanaarachchi, Sevvandi; Muñoz, Mario A.; Hyndman, Rob J.; Smith-Miles, Kate: On normalization and algorithm selection for unsupervised outlier detection (2020)
  18. Lopes, Miles E.: Estimating a sharp convergence bound for randomized ensembles (2020)
  19. Lu, Haihao; Mazumder, Rahul: Randomized gradient boosting machine (2020)
  20. Mišić, Velibor V.: Optimization of tree ensembles (2020)

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