A validation set is a subset of the data used to tune the parameters of a machine learning model and assess its performance during the training process. It helps in determining how well the model generalizes to unseen data, allowing for adjustments to avoid overfitting and ensuring the model's robustness. The use of a validation set is crucial when implementing data augmentation techniques, as it aids in understanding how these modifications influence model performance.
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