You might want to let the user decide if it is more important to have a false positive or a false negative. For some applications a false alarm is a minor nuis

You might want to let the user decide if it is more important to have a false positive or a false negative. For some applications a false alarm is a minor nuisance but a false negative is catastrophic, but for some applications it is flipped. In the past I have let the end user define the balance (i.e. "a false negative is 10X as bad as a false positive") and the decision results were scaled by their decision rule. It's not always easy to do as many machine learning algorithms are nonlinear but at least you can cast a wider net of potential customers.