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Simultaneous regression shrinkage, variable selection and clustering of predictors with OSCAR
In this paper, a new method called the OSCAR (Octagonal Shrinkage and Clustering Algorithm for Regression) is proposed to simultaneously select variables and perform supervised clustering in the context of linear regression. The technique is based on penalized least squares with a geometrically intu...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2007
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2605279/ https://ncbi.nlm.nih.gov/pubmed/17608783 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/j.1541-0420.2007.00843.x |
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