The F-score, also known as the F-measure or F1 score, is a statistical measure used to evaluate the performance of a binary classification model. It combines both precision and recall into a single metric to provide a more balanced view of a model's performance, particularly in situations where the class distribution is imbalanced. ### Key Components: 1. **Precision**: This measures the accuracy of the positive predictions.
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