Quite often in Data Science we deal with use cases where the penalty for False Negative can be huge. Examples can be missing to predict having a disease, denying loan based on false prediction, not acting on a cyber threat etc. So the question is what kind of techniques exist to minimize or eliminate false negatives?
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