Also known as: false positive (FP) Β· FP
False Positive (FP) is an error in which a model predicts the positive class when the true class is negative. In practice, it means the system flags a condition, event, or item as present when it is not.
An example in which the model mistakenly predicts the positive class. For example, the model predicts that a particular email message is spam (the positive class), but that email message is actually not spam. See Thresholds and the confusion matrix in Machine Learning Crash Course for more information.