Definition False negative

Machine learning algorithms can be used to classify an object into two different categories. For instance, spam filters can be used to scan e-mails and identify them as legitimate ("not spam") or unsolicited ("spam”). In this context, a negative classification is the correct identification and sorting of a legitimate e-mail item into the “not spam” category. A false negative is the misindentification and sorting of an unsolicited e-mail item into the legitimate (“not spam”) e-mail category.