Validation accuracy is the metric that indicates how well a machine learning model performs on a validation dataset, which is separate from the training dataset. It serves as a crucial measure to evaluate the generalization ability of a model, reflecting its accuracy in making predictions on unseen data. This concept is essential for identifying overfitting, ensuring that the model not only memorizes the training data but also can make accurate predictions on new data.
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