Machine Learning Resources

What is False Positive Rate (FPR)?

The false positive rate measures the proportion of actual negative observations that were predicted to be positive. In other words, it is 1 – Specificity, or

False Positive Rate = False Positives / (False Positives + True Negatives)

Using an example:

Confusion Matrix

FPR = 60 / (60 + 100) = .375

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