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Computing Leapfrog Regularization Paths with Applications to Large-Scale K-mer Logistic Regression
High-dimensional statistics deals with statistical inference when the number of parameters or features p exceeds the number of observations n (i.e., [Formula: see text]). In this case, the parameter space must be constrained either by regularization or by selecting a small subset of [Formula: see te...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Mary Ann Liebert, Inc., publishers
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219187/ https://www.ncbi.nlm.nih.gov/pubmed/33739865 http://dx.doi.org/10.1089/cmb.2020.0284 |