High Precision value and low recall value - Logistic regression

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I'm trying to understand logistic regression and very confused when to use high precision value and low regression value. Can you please explain this with an example?
Jun 13 in Python by Kamal
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1 answer to this question.

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You use high positive and low recall in situations where you have to reduce the number of false positive. For example, you have an image and you wish to see people's reaction and categorize them amongst positive reaction and negative reaction. If keeping the positive reaction precise is our aim, then we should choose high precision and low recall.
answered Jun 13 by Greg

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