a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data

257734638). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding Information: We thank KWS for providing the maize datasets. We thank the Centre for Mathematical Analysis, Geometry, and Dynamical Systems, from Instituto Superior Técnico (IST) of the University of Lisbon, for granting access to their computing resources to run the Deep Learning Models. Publisher Copyright: © The Author(s) 2024.