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Alternative stopping rules to limit tree expansion for random forest models

Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independent variables. There are relatively few adjustable h...

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Detalles Bibliográficos
Autores principales: Little, Mark P., Rosenberg, Philip S., Arsham, Aryana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448733/
https://www.ncbi.nlm.nih.gov/pubmed/36068261
http://dx.doi.org/10.1038/s41598-022-19281-7

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