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Seagull: lasso, group lasso and sparse-group lasso regularization for linear regression models via proximal gradient descent
BACKGROUND: Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalization approaches are often the methods of choice. They are especially useful in case of multicollinearity, which appears if th...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493359/ https://www.ncbi.nlm.nih.gov/pubmed/32933477 http://dx.doi.org/10.1186/s12859-020-03725-w |