From a conceptual standpoint I understand the trade off involved with the ROC curve. You can increase the accuracy of true positive predictions but you will be taking on more false positives and vise versa.
I wondering how one would target a specific point on the curve for a Logistic Regression model? Would you just raise the probability threshold for what would constitute a 0 or a 1 in the regression? (Like shifting at what probability predictions start to get marked as one. ex: shifting the point predictions get marked 1 from 0.5 to 0.6)
I have a feeling it isn't that simple, but if it is how would you know which threshold to target to reach a specific point on the curve?