Glossary term
Glossary term
Foundations
An example in which the model mistakenly predicts the negative class. For example, the model predicts that a particular email message is not spam (the negative class), but that email message actually is spam.
Created for this library
A medical screening team monitors false negatives carefully because a missed cancer case has a far higher cost than a false positive.
A cybersecurity team tracks false negatives on its intrusion detector because missed attacks can lead to costly breaches.
A fraud team reports false negatives weekly so the operations team can compare missed fraud value against the cost of false declines.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License