Natural Language Processing
A test set is a portion of a dataset that is used to evaluate the performance of a machine learning model after it has been trained. It is essential in assessing how well the model generalizes to new, unseen data and helps to prevent overfitting by providing a separate evaluation benchmark. Using a test set allows for the measurement of accuracy, precision, recall, and other performance metrics to ensure the model's effectiveness in real-world applications.
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