Let's return to the dog-fox data. Your task is to predict, if there is a fox (F) in a picture. You've trained a classifier and got first predictions. Now you'd like to build a confusion matrix, so your task is to count all false negative predictions.
| True | F | F | D | D | D | F | D | D | F | F |
| Predicted | F | D | D | F | F | D | D | D | D | F |