F1 score

The F1 Score is a statistical measure used to evaluate the accuracy of a binary classification model. It considers both the precision (the accuracy of positive predictions) and the recall (the ability to find all relevant instances) of the model. The F1 Score is the harmonic mean of precision and recall, providing a balance between them. It is particularly useful when the classes are imbalanced.