Answer Posted / Amrit Lal Meena

A validation set is used during the training process to tune hyperparameters and select the best model. It helps prevent overfitting by providing an unbiased estimate of the model's performance. A test set, on the other hand, is only used at the end of the model selection process to evaluate the final model's generalization ability to new data. The difference between them lies in their use: validation for tuning and testing for evaluation.

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