(Written with Claude-3.5-Sonnet. I have checked and edited the content. -Joni) Summary of the Issue The holdout paradigm, commonly implemented as a train-test split, is a fundamental technique in machine learning for assessing model performance. However, when applied to cross-sectional data, it can lead to significant challenges in terms of model generalizability. Cross-sectional data, by its nature, provides a snapshot…
Associate Professor (tenure track) at the University of Vaasa, and Adjunct Professor at the Turku School of Economics. Based in Finland.