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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...
Gardado en:
| Publicado en: | Comput Math Methods Med |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Hindawi
2017
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| Assuntos: | |
| Acceso en liña: | 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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