Precision
AI/ML Fundamentals
Of predicted positives, how many are actually positive
What is Precision?
Precision = True Positives / (True Positives + False Positives). Answers "When it predicts yes, how often is it right?"
Real-World Examples
- •Spam filter: of emails marked spam, 95% are actually spam
- •Medical test with low false positives
When to Use This
When false positives are costly (e.g., marking good emails as spam)
Related Terms
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