False Negative (FN)

What is a False Negative (FN)?

When evaluating the prediction of a model given a sample, a False Negative (FN) is the outcome where the model incorrectly predicts the negative class.

Consider the example of a model which classifies emails as either spam (positive class) or not spam (negative class). If the actual label of the sample is spam but the model predicts not spam then this outcome will be considered a False Negative.

Related Terms