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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Detalles Bibliográficos
Autores principales: Thomas, Janek, Hepp, Tobias, Mayr, Andreas, Bischl, Bernd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5555005/
https://www.ncbi.nlm.nih.gov/pubmed/28831289
http://dx.doi.org/10.1155/2017/1421409

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5555005/
https://www.ncbi.nlm.nih.gov/pubmed/28831289
http://dx.doi.org/10.1155/2017/1421409

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