Answer Posted / Priya Yadav

F1 score is the harmonic mean of precision and recall, and it provides a balanced evaluation metric for classification problems. It is calculated by taking the average of precision and recall weighted by their reciprocals. F1 score ranges from 0 to 1, with higher values indicating better performance. We can use F1 score to compare multiple classifiers or to evaluate the performance of a single classifier on multiple classes.

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