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Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction
BACKGROUND: Statistical boosting is a computational approach to select and estimate interpretable prediction models for high-dimensional biomedical data, leading to implicit regularization and variable selection when combined with early stopping. Traditionally, the set of base-learners is fixed for...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447543/ https://www.ncbi.nlm.nih.gov/pubmed/34530737 http://dx.doi.org/10.1186/s12859-021-04340-z |