The f-measure is a statistical metric used to evaluate the accuracy of a binary classification model, combining both precision and recall into a single score. It is particularly useful in scenarios where there is an uneven class distribution or when false positives and false negatives have different consequences. By providing a balance between precision (the accuracy of positive predictions) and recall (the ability to find all relevant instances), the f-measure helps assess the overall performance of an information retrieval system.
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