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Reliable estimation of prediction errors for QSAR models under model uncertainty using double cross-validation
BACKGROUND: Generally, QSAR modelling requires both model selection and validation since there is no a priori knowledge about the optimal QSAR model. Prediction errors (PE) are frequently used to select and to assess the models under study. Reliable estimation of prediction errors is challenging – e...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer International Publishing
2014
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4260165/ https://www.ncbi.nlm.nih.gov/pubmed/25506400 http://dx.doi.org/10.1186/s13321-014-0047-1 |