Using and understanding cross-validation strategies. Perspectives on Saeb et al

Max A. Little, Gael Varoquaux, Sohrab Saeb, Luca Lonini, Arun Jayaraman, David C Mohr, Konrad P. Kording

Research output: Contribution to journalComment/debatepeer-review

58 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1-6
Number of pages6
Issue number5
StatePublished - May 1 2017


  • clinical applications
  • cross-validation
  • machine learning

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications


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