How to do prediction in a binary classification with logistic regression when we care much more about type I error than type II error? Which criteria should I use to select the threshold value and how should I show different altitude to type I error and type II error?
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If you could quantify the penalty you would pay for a type I error and the penalty you would pay for a type II error, can you select the threshold to minimize the expected penalty? – littleO Dec 25 '18 at 08:07