rpart

R package rpart: Recursive Partitioning. Recursive partitioning and regression trees. Recursive partitioning for classification, regression and survival trees. An implementation of most of the functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.

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References in zbMATH (referenced in 152 articles )

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  1. Blanquero, Rafael; Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: On sparse optimal regression trees (2022)
  2. Kim, Ahhyoun; Kim, Hyunjoong: A new classification tree method with interaction detection capability (2022)
  3. Wang, Hengjie; Planas, Robert; Chandramowlishwaran, Aparna; Bostanabad, Ramin: Mosaic flows: a transferable deep learning framework for solving PDEs on unseen domains (2022)
  4. Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan: SIRUS: stable and interpretable RUle set for classification (2021)
  5. Blanquero, Rafael; Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Optimal randomized classification trees (2021)
  6. Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Mathematical optimization in classification and regression trees (2021)
  7. Conde, David; Fernández, Miguel A.; Rueda, Cristina; Salvador, Bonifacio: Isotonic boosting classification rules (2021)
  8. da Silva, Natalia; Cook, Dianne; Lee, Eun-Kyung: A projection pursuit forest algorithm for supervised classification (2021)
  9. Farkas, Sébastien; Lopez, Olivier; Thomas, Maud: Cyber claim analysis using generalized Pareto regression trees with applications to insurance (2021)
  10. Günlük, Oktay; Kalagnanam, Jayant; Li, Minhan; Menickelly, Matt; Scheinberg, Katya: Optimal decision trees for categorical data via integer programming (2021)
  11. 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)
  12. Krzysztof Gajowniczek, Tomasz Ząbkowski: ImbTreeEntropy: An R package for building entropy-based classification trees on imbalanced datasets (2021) not zbMATH
  13. Krzysztof Gajowniczek; Tomasz Ząbkowski: ImbTreeAUC: An R package for building classification trees using the area under the ROC curve (AUC) on imbalanced datasets (2021) not zbMATH
  14. Oune, Nicholas; Bostanabad, Ramin: Latent map Gaussian processes for mixed variable metamodeling (2021)
  15. Beaulac, Cédric; Rosenthal, Jeffrey S.: BEST: a decision tree algorithm that handles missing values (2020)
  16. 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
  17. Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani: Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties (2020) arXiv
  18. Blanquero, Rafael; Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Sparsity in optimal randomized classification trees (2020)
  19. Bommert, Andrea; Sun, Xudong; Bischl, Bernd; Rahnenführer, Jörg; Lang, Michel: Benchmark for filter methods for feature selection in high-dimensional classification data (2020)
  20. Chakraborty, Tanujit; Ghosh, Indrajit: Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: a data-driven analysis (2020)

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