Precision and Recall

This blog is to introduce some important classifier metrics: precision and recall. The precision of the classifier is the accuracy of the positive predictions. Another metric, recall, also called sensitivity or the true positive rate (TPR), is the ratio of positive instances that are correctly detected by the classifier. To compare binary classifiers, it is convenient to use the F1 score, which is the harmonic mean of precision and recall. Whereas the regular mean treats all values equally, the harmonic mean gives much more weight to low values.