References in zbMATH (referenced in 142 articles )

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  1. Kim, Ahhyoun; Kim, Hyunjoong: A new classification tree method with interaction detection capability (2022)
  2. Bénard, Clément; Biau, Gérard; Da Veiga, Sébastien; Scornet, Erwan: SIRUS: stable and interpretable RUle set for classification (2021)
  3. Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Mathematical optimization in classification and regression trees (2021)
  4. Conde, David; Fernández, Miguel A.; Rueda, Cristina; Salvador, Bonifacio: Isotonic boosting classification rules (2021)
  5. Farkas, Sébastien; Lopez, Olivier; Thomas, Maud: Cyber claim analysis using generalized Pareto regression trees with applications to insurance (2021)
  6. Günlük, Oktay; Kalagnanam, Jayant; Li, Minhan; Menickelly, Matt; Scheinberg, Katya: Optimal decision trees for categorical data via integer programming (2021)
  7. 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)
  8. Krzysztof Gajowniczek, Tomasz Ząbkowski: ImbTreeEntropy: An R package for building entropy-based classification trees on imbalanced datasets (2021) not zbMATH
  9. 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
  10. Beaulac, Cédric; Rosenthal, Jeffrey S.: BEST: a decision tree algorithm that handles missing values (2020)
  11. 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
  12. Benjamin G. Stokell, Rajen D. Shah, Ryan J. Tibshirani: Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties (2020) arXiv
  13. Blanquero, Rafael; Carrizosa, Emilio; Molero-Río, Cristina; Romero Morales, Dolores: Sparsity in optimal randomized classification trees (2020)
  14. Bommert, Andrea; Sun, Xudong; Bischl, Bernd; Rahnenführer, Jörg; Lang, Michel: Benchmark for filter methods for feature selection in high-dimensional classification data (2020)
  15. Genuer, Robin; Poggi, Jean-Michel: Random forests with R (2020)
  16. Gupta, Bhisham C.; Guttman, Irwin; Jayalath, Kalanka P.: Statistics and probability with applications for engineers and scientists using MINITAB, R and JMP (2020)
  17. Han, Sunwoo; Kim, Hyunjoong; Lee, Yung-Seop: Double random forest (2020)
  18. Madan Gopal Kundu, Samiran Ghosh: Survival trees for right-censored data based on score based parameter instability test (2020) arXiv
  19. Nicolas R. Lauve, Stuart J. Nelson, S. Stanley Young, Robert L. Obenchain, Christophe G. Lambert: LocalControl: An R Package for Comparative Safety and Effectiveness Research (2020) not zbMATH
  20. Ribeiro, Rita P.; Moniz, Nuno: Imbalanced regression and extreme value prediction (2020)

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