Page 295 about binary classification

[Deleetdk]

A more sophisticated approach looks at the distribution of predictions, and makes
an informed trade-off between true positive (in this context also known as recall and hit
rate), and accuracy (i.e., the false positive rate).

https://en.wikipedia.org/wiki/Sensitivity_and_specificity

I think you mean specificity, not accuracy. Accuracy is not the false positive rate (accuracy = (TP + TN) / TP + TN + FP + FN). The trade-off when selecting threshold is between TPR (sensitivity) and TNR (specificity).

[Derek-Jones]

That sentence needs to be reworked.

General discussion tends to be about true/false positives, while technical discussions revolve around recall/precision or other pairs of measures.