Answer:
False negative
Explanation:
A false negative may be defined as the outcome where the outcome of the binary classification process the model incorrectly determines or predicts the negative class.
In the context, though the employee have access to open the door as a part of his job, the employee could not open the door by scanning his badge. So this may be considered as a false negative as the employee could not open the door inspite of having access to the door.
