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Probing for Sparse and Fast Variable Selection with Model-Based Boosting
We present a new variable selection method based on model-based gradient boosting and randomly permuted variables. Model-based boosting is a tool to fit a statistical model while performing variable selection at the same time. A drawback of the fitting lies in the need of multiple model fits on slig...
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| Опубликовано в: : | Comput Math Methods Med |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Hindawi
2017
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5555005/ https://ncbi.nlm.nih.gov/pubmed/28831289 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/1421409 |
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