F-measure (F1 Score)

The F-measure, also known as the F1 score, is a metric used to evaluate a model's performance, especially when dealing with imbalanced datasets. It combines a model's precision (how many selected items are relevant) and recall (how many relevant items are selected) into a single score. A higher F-measure indicates a better balance between precision and recall.