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Set the threshold by comparing the expected cost of action with the expected cost of not acting. The best threshold is the point where acting on a prediction produces more expected value than ignoring it or sending it for review.

There is no universal target. A model is good enough when its decisions create more value than the current process after accounting for false positives, false negatives, intervention costs, and review capacity.

Prioritize the metric that matches the more expensive error. If missing a positive case is costly, favor recall. If unnecessary action is costly, favor precision. Many business systems use different thresholds for automatic action and human review.