Open AccessUsing and understanding cross-validation strategies. Perspectives on Saeb et al.
Author(s) -
Max A. Little,
Gaël Varoquaux,
Sohrab Saeb,
Luca Lonini,
Arun Jayaraman,
David C. Mohr,
Konrad Kording
Publication year - 2017
Publication title -
gigascience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/gix020
Subject(s) - interpretation (philosophy) , computer science , test (biology) , artificial intelligence , biology , programming language , ecology
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.