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Optimally splitting cases for training and testing high dimensional classifiers
BACKGROUND: We consider the problem of designing a study to develop a predictive classifier from high dimensional data. A common study design is to split the sample into a training set and an independent test set, where the former is used to develop the classifier and the latter to evaluate its perf...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2011
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3090739/ https://www.ncbi.nlm.nih.gov/pubmed/21477282 http://dx.doi.org/10.1186/1755-8794-4-31 |