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Nested leave-two-out cross-validation for the optimal crop yield model selection
Geoscientific Model Development
The use of statistical models to study the impact of weather on crop yield has not ceased to increase. Unfortunately, this type of application is characterized by datasets with a very limited number of samples (typically one sample per year). In general, statistical inference uses three datasets: the training dataset to optimize the model parameters, the validation dataset to select the best model, and the testing dataset to evaluate the model generalization ability. Splitting the overalldoi:10.5194/gmd-15-3519-2022 doaj:83b09203a19a4bc090f64910c94c686e fatcat:22j24yc24baetdrcvqy5z6uuzm