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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...
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| Pubblicato in: | BMC Bioinformatics |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7493359/ https://ncbi.nlm.nih.gov/pubmed/32933477 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03725-w |
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