Optimal hyperparameter tuning of random forests for estimating causal treatment effects
Recent studies have expanded the focus of machine learning methods like random forests beyond prediction. They have found utility in the area of causal inference by using it to estimate propensity scores. It has also been established in the literature that tuning the hyperparameter values of rando...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Prince of Songkla University
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/66666c37aa284b68b145f52e104a4618 |
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