Input
output(str): The generated text (set of predicted positive items)expectedOutput(str): The reference text (set of ground-truth positive items)
Output
Result(float): A score between 0 and 1.
Interpretation
- Higher scores (closer to 1): A larger fraction of predicted positives are correct (fewer false positives)
- Lower scores (closer to 0): Many predicted positives are incorrect (more false positives)
Formula
This is a Similarity Metric
Use Cases
- Information retrieval and search relevance
- Classification tasks where avoiding false alarms is critical
- Evaluating the relevance of generated content