Measuring the bias of incorrect application of feature selection when using cross-validation in radiomics
Abstract Background Many studies in radiomics are using feature selection methods to identify the most predictive features. At the same time, they employ cross-validation to estimate the performance of the developed models. However, if the feature selection is performed before the cross-validation,...
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| Formato: | article |
| Lenguaje: | EN |
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SpringerOpen
2021
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| Acceso en línea: | https://doaj.org/article/e05fc95b049c4fdc8f28b17d1566ac18 |
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