What Does False Negatives Mean?
False negatives are one of four components in a classical confusion matrix for binary classification. In binary classification, two types or classes are analyzed by a machine learning program or similar technology.
Techopedia Explains False Negatives
The idea with the confusion matrix is that engineers have the actual values on the test data in hand. Then they run the machine learning program, and it makes its predictions. If the prediction matches what is known, that is a successful outcome. If it doesn’t, that’s not a successful outcome.
