The supervised classification algorithm you pick will usually output a real-valued score, and you will decide upon to select out a threshold or thresholds above which to block the exercise or exhibit...

The supervised classification algorithm you pick will usually output a real-valued score, and you will decide upon to select out a threshold or thresholds above which to block the exercise or exhibit off increased friction. How do you select out out this threshold?

Now replicate onconsideration on that you have two versions of your mannequin with one-of-a-kind parameters(e.g., extraordinarily correct regularization) or even special mannequin households (e.g., logistic regression versus random forest). Which one is better?