interview question
Question
Is it better to have too many false positives or too many false negatives? Explain
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Machine Learning
55 years
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Answer ( 1 )
I think it depends on the nature of the problem, in case of a problem related to targeting getting lesser of inclusion error (False Positive) compared to exclusion error (False Negative) may be better.