“…One of the main tasks in the prediction workflow is to evaluate the generalization performance of machine learning algorithms using an appropriate resampling procedure.
‐fold cross‐validation is a widely used resampling technique that can be used to balance the bias and variance, and estimate the out‐of‐sample predictive performance of machine learning models (Agarwal, Tang, Narayanan & Zhuang,
2020; Alipour, Mukherjee, & Nateghi,
2019; Hastie et al., 2009; James et al.,
2013; Jung,
2018; Mukherjee & Nateghi,
2019,
2017; Obringer, Mukherjee, & Nateghi,
2020). This approach involves randomly dividing the set of observations into
‐folds of approximately equal sizes.…”