Accuracy, precision, recall, and F1-score are metrics used to assess automatic classifiers. These metrics are calculated from a confusion matrix. Say we have spam filter which tells whether a mail is spam or not. With a test dataset of 100 spam emails and 900 non-spam, we get the following results.
(Machine) Learning log.