Bias in error estimation when using cross-validation for model selection

BACKGROUND: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the...

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Detalles Bibliográficos
Autores principales: Varma, Sudhir, Simon, Richard
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1397873/
https://www.ncbi.nlm.nih.gov/pubmed/16504092
http://dx.doi.org/10.1186/1471-2105-7-91

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1397873/
https://www.ncbi.nlm.nih.gov/pubmed/16504092
http://dx.doi.org/10.1186/1471-2105-7-91

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