On the Capability of Classification Trees and Random Forests to Estimate Probabilities

Author:

Plante Jean-FrançoisORCID,Radatz Marisa

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Reference32 articles.

1. Zhao P, Su X, Ge T, Fan J (2016) Propensity score and proximity matching using random forest. Contemp Clin Trials 47:85–92

2. Westreich D, Lessler J, Funk MJ (2010) Propensity score estimation: machine learning and classification methods as alternatives to logistic regression. J Clin Epidemiol 63(8):826–833

3. Gelein B, Haziza D, Causeur D (2018) Propensity weighting for survey nonresponse through machine learning. In: 13es Journées de méthodologie statistique de l’Insee (JMS), Paris, France. hal-02076739

4. Breiman L (1996) Out-of-bag estimation. Technical report, University of California at Berkeley

5. Tremblay V, Plante J-F, Trempe-Martineau J (2023) Équité des algorithmes d’aide à la décision: perspective interdisciplinaire et recommendations. Unpublished technical report

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