Definition
A false positive is a negative case that a classifier or detector incorrectly labels as positive. A legitimate transaction blocked as fraud, safe code reported as vulnerable, and a human-written essay flagged as AI-generated are all false positives. Which outcome counts as "positive" is a convention and must be stated.
Do not confuse the count with the false positive rate. The rate is false positives / (false positives + true negatives), so its denominator is all actually negative cases. Precision uses a different denominator: all predicted positive cases.
The right threshold depends on consequences. A low threshold may catch more real problems while sending more harmless cases to review. Teams should report both sides of that tradeoff and identify who bears the cost of a false alarm.
Distinguish it from nearby terms
- A false negative is a positive case incorrectly labeled negative.
- A true positive is a positive case correctly detected.
- A false discovery is a positive prediction that proves wrong. Its rate is related to precision, not to the false positive rate's denominator.
Check your understanding
A security scanner flags 20 of 1,000 safe files and 80 of 100 unsafe files. What is its false positive rate, and what other rate describes the unsafe files it missed?