These are also primary metrics and are more often used than accuracy or error rate for imbalanced test sets, e.g., the majority of the test samples have one class label. Precision and recall for binary classification are defined as below. The F1 score is the harmonic mean of the precision and recall, as in Eq. 3. An F1 score reaches its best value at 1 (perfect precision and recall) and worst at 0.