Validation accuracy refers to the measure of how well a model performs on a validation dataset, which is separate from the training data used to build the model. This metric provides insights into the model's ability to generalize to unseen data, highlighting its effectiveness in making predictions. A high validation accuracy indicates that the model can successfully apply what it has learned from training, while also being sensitive to issues like overfitting or underfitting, which can be addressed through various strategies and techniques.
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