AI Glossary Term
What does “False Negative” mean?
Definition
An incorrect prediction where a model misses a true positive case.
How False Negative works
Example
A cancer-screening model looks at a scan that does contain a tumor but says 'no finding'. That is a false negative. In screening, these misses are often considered more costly than false alarms.
Why it matters
Which error is worse depends on the task. Understanding false negatives helps decide thresholds and when human review is needed.
Common questions
How is a false negative different from a false positive?
A false negative misses something that is there. A false positive flags something that is not.
Which metric reflects false negatives?
Recall: it drops as false negatives rise.
Can I reduce false negatives?
Usually by lowering the decision threshold, which tends to raise false positives. Trade-offs are unavoidable.