Artificial intelligence · Grades 9–12
Recall from true positives and false negatives
The denominator counts actual positives, not predicted positives.
Method and conditions
The denominator counts actual positives, not predicted positives.
recall = TP/(TP+FN)
Worked examples
A binary classifier has TP=8 and FN=51. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Of 59 actual positives, 8 were detected.
0.1356
A binary classifier has TP=53 and FN=62. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Of 115 actual positives, 53 were detected.
0.4609
Try it
A binary classifier has TP=52 and FN=16. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
A binary classifier has TP=13 and FN=56. Calculate positive-class recall as a fraction between 0 and 1. Round the final result to 4 decimal places if needed.
Check your work
Answers and marking notes
- 0.7647
Of 68 actual positives, 52 were detected.
- 0.1884
Of 69 actual positives, 13 were detected.
Further reading and review references
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