Department of Mathematics, Astun University, Aston Triangle, B4 7ET, Birmingham, UK.
Parietal, INRIA, NeuroSpin, bat 145 CEA Saclay, 91191, Gif sur Yvette, France.
Gigascience. 2017 May 1;6(5):1-6. doi: 10.1093/gigascience/gix020.
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.
这篇由三部分组成的综述详细探讨了交叉验证的复杂性,这是由对 Saeb 等人题为“临床机器学习中需要近似用例”的论文的同行评审所促成的。它包含了评审者和原始作者对交叉验证的观点:不同策略的适用性及其解释。