Glossary term
Glossary term
Foundations
The proportion of actual negative examples for which the model mistakenly predicted the positive class. The following formula calculates the false positive rate:
The false positive rate is the x-axis in an ROC curve.
See Classification: ROC and AUC in Machine Learning Crash Course for more information.
Created for this library
A fraud team caps its false positive rate at half a percent to limit customer friction from incorrect declines.
An email security team requires false positive rate below 0.1 percent on its phishing detector before each rollout.
A medical screening team reports false positive rate alongside recall when proposing a new threshold for a screening test.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License