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Fitting Penalized Logistic Regression Models Using QR Factorization
The paper presents improvement of a commonly used learning algorithm for logistic regression. In the direct approach Newton method needs inversion of Hessian, what is cubic with respect to the number of attributes. We study a special case when the number of samples m is smaller than the number of at...
Gorde:
| Argitaratua izan da: | Computational Science – ICCS 2020 |
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| Egile Nagusiak: | , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2020
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7302851/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-50417-5_4 |
| Etiketak: |
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