F1 Score: Difference between revisions
Thakshashila (talk | contribs) Created page with "= F1 Score = The '''F1 Score''' is a performance metric used in classification problems that balances the trade-off between Precision and Recall (also known as Sensitivity). It is especially useful when the dataset is imbalanced, and both false positives and false negatives are important. == Definition == The F1 Score is the '''harmonic mean''' of Precision and Recall. :<math> F1 = 2 \cdot \frac{\text{Precision} \cdot \text{Recall}}{\text{Precision} + \te..." |
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f1 score in machine learning, f1 score formula, harmonic mean of precision and recall, model evaluation metrics, f1 score example, f1 vs accuracy, precision recall f1 trade-off | f1 score in machine learning, f1 score formula, harmonic mean of precision and recall, model evaluation metrics, f1 score example, f1 vs accuracy, precision recall f1 trade-off | ||
[[Category:Artificial Intelligence]] | |||