A training, validation, and test split separates data used to fit parameters, choose models or settings, and estimate final generalization. This guide explains the mechanism, trade-offs, evaluation, and controls that matter in practice.
A training, validation, and test split separates data used to fit parameters, choose models or settings, and estimate final generalization. This guide explains the mechanism, trade-offs, evaluation, and controls that matter in practice.