Artificial intelligence · Grades 9–12
Precision from true and false positives
The denominator counts predicted positives. This generator always gives a nonzero denominator.
Method and conditions
The denominator counts predicted positives. This generator always gives a nonzero denominator.
precision = TP/(TP+FP)
Worked examples
A binary classifier has TP=37 and FP=67. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Of 104 positive predictions, 37 are correct.
0.3558
A binary classifier has TP=84 and FP=73. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Of 157 positive predictions, 84 are correct.
0.535
Try it
A binary classifier has TP=38 and FP=27. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
A binary classifier has TP=79 and FP=41. Calculate positive-class precision as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Check your work
Answers and marking notes
- 0.5846
Of 65 positive predictions, 38 are correct.
- 0.6583
Of 120 positive predictions, 79 are correct.
Further reading and review references
These are reference links, not copied exercises, institutional endorsement or proof of independent review.
AI-assisted preview; independent educational review required. Level labels describe prerequisites, not accreditation or official curriculum alignment.