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

Journal: GigaScience
Published Date:

Abstract

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.

Authors

  • Max A Little
    Aston University, Aston Triangle, Birmingham, United Kingdom.
  • Gael Varoquaux
    Parietal, INRIA, NeuroSpin, bat 145 CEA Saclay, 91191, Gif sur Yvette, France.
  • Sohrab Saeb
    Center for Behavioral Intervention Technologies, Department of Preventive Medicine, Northwestern University, Chicago, Illinois, United States of America.
  • Luca Lonini
    Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL 60611 USA.
  • Arun Jayaraman
    Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL 60611 USA.
  • David C Mohr
    Northwestern University, USA.
  • Konrad P Kording
    Departments of Bioengineering and Neuroscience,University of Pennsylvania,Philadelphia,PA 19104.kording@upenn.eduwww.kordinglab.com.