A false negative occurs when a model fails to predict the presence of an object that actually exists in the input data. This means the model incorrectly classifies the object as "absent" or "non-existent" despite its real-world presence.
A false negative occurs when a model fails to predict the presence of an object that actually exists in the input data. This means the model incorrectly classifies the object as "absent" or "non-existent" despite its real-world presence.