Algorithm

F1 Score

Description

The F1 Score is the harmonic mean of Precision and Recall. It provides a single metric that balances both the concerns of false positives and false negatives. It is particularly useful when you need to take both Precision and Recall into account, especially if there is an uneven class distribution.

$$ F1 = 2 \times \frac{\text{Precision} \times \text{Recall}}{\text{Precision} + \text{Recall}} $$

Use Cases

Imbalanced Datasets