# False Positive Error Rate

(Redirected from false positive rate (fpr))

A False Positive Error Rate is a binary classification performance measure that is based on the Probability that a Predictive Relation will Incorrectly Predict that a False Test Instance is a True Test Instance (i.e. make a Positive Prediction).

• AKA: FPR, Type 1 Error Rate.
• Context:
• It can be estimated by: FP/(FP+TN)
• Example(s):
• The probability that a patient without disease $\displaystyle{ X }$ will receive a test result that claims they do have disease X.
• Counter-Example(s):
• See: Type 1 Error, False Discovery Rate.

## References

### 2009

• (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Type_I_and_type_II_errors#Type_I_error
• QUOTE: Type I error, also known as an "error of the first kind", an $\displaystyle{ α }$ error, or a "false positive": the error of rejecting a null hypothesis when it is actually true. Plainly speaking, it occurs when we are observing a difference when in truth there is none. An example of this would be if a test shows that a woman is pregnant when in reality she is not. Type I error can be viewed as the error of excessive credulity.