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Bootstrapping the out-of-sample predictions for efficient and accurate cross-validation
Cross-Validation (CV), and out-of-sample performance-estimation protocols in general, are often employed both for (a) selecting the optimal combination of algorithms and values of hyper-parameters (called a configuration) for producing the final predictive model, and (b) estimating the predictive pe...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6191021/ https://www.ncbi.nlm.nih.gov/pubmed/30393425 http://dx.doi.org/10.1007/s10994-018-5714-4 |