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Using and understanding cross-validation strategies. Perspectives on Saeb et al.
This three-part review takes a detailed look at the complexities of cross-validation, fostered by the peer review of Saeb et al.’s paper entitled “The need to approximate the use-case in clinical machine learning.” It contains perspectives by reviewers and by the original authors that touch upon cro...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5441396/ https://www.ncbi.nlm.nih.gov/pubmed/28327989 http://dx.doi.org/10.1093/gigascience/gix020 |
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author | Little, Max A Varoquaux, Gael Saeb, Sohrab Lonini, Luca Jayaraman, Arun Mohr, David C Kording, Konrad P |
author_facet | Little, Max A Varoquaux, Gael Saeb, Sohrab Lonini, Luca Jayaraman, Arun Mohr, David C Kording, Konrad P |
author_sort | Little, Max A |
collection | PubMed |
description | This three-part review takes a detailed look at the complexities of cross-validation, fostered by the peer review of Saeb et al.’s paper entitled “The need to approximate the use-case in clinical machine learning.” It contains perspectives by reviewers and by the original authors that touch upon cross-validation: the suitability of different strategies and their interpretation. |
format | Online Article Text |
id | pubmed-5441396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54413962017-06-19 Using and understanding cross-validation strategies. Perspectives on Saeb et al. Little, Max A Varoquaux, Gael Saeb, Sohrab Lonini, Luca Jayaraman, Arun Mohr, David C Kording, Konrad P Gigascience Review This three-part review takes a detailed look at the complexities of cross-validation, fostered by the peer review of Saeb et al.’s paper entitled “The need to approximate the use-case in clinical machine learning.” It contains perspectives by reviewers and by the original authors that touch upon cross-validation: the suitability of different strategies and their interpretation. Oxford University Press 2017-03-17 /pmc/articles/PMC5441396/ /pubmed/28327989 http://dx.doi.org/10.1093/gigascience/gix020 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Little, Max A Varoquaux, Gael Saeb, Sohrab Lonini, Luca Jayaraman, Arun Mohr, David C Kording, Konrad P Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title | Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title_full | Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title_fullStr | Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title_full_unstemmed | Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title_short | Using and understanding cross-validation strategies. Perspectives on Saeb et al. |
title_sort | using and understanding cross-validation strategies. perspectives on saeb et al. |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5441396/ https://www.ncbi.nlm.nih.gov/pubmed/28327989 http://dx.doi.org/10.1093/gigascience/gix020 |
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