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Machine Learning Resources

What is False Positive Rate (FPR)?

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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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