Table A.1.
Generic confusion matrix for a binary classification problem.
| Predictions |
|||
|---|---|---|---|
| Positive | Negative | ||
| True | Positive | TP | FN |
| Negative | FP | TN | |
Notes. In a confusion matrix, columns indicate the number of objects per class, as predicted by the classifier, while rows are referred to the true (known) objects per class. Hence, the main diagonal terms report the number of correctly classified objects for each class. While, the terms FP and FN count, respectively, the false positives and false negative quantities.
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