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eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models
BACKGROUND: Regularized generalized linear models (GLMs) are popular regression methods in bioinformatics, particularly useful in scenarios with fewer observations than parameters/features or when many of the features are correlated. In both ridge and lasso regularization, feature shrinkage is contr...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2019
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469092/ https://www.ncbi.nlm.nih.gov/pubmed/30991955 http://dx.doi.org/10.1186/s12859-019-2778-5 |