What is a false positive rate?
The proportion of actual negative examples for which the model mistakenly predicted the positive class.
false positive rate explained in plain English
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.
Example
Practitioners refer to false positive rate when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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