Question: Imagine you've built a predictive model for customer churn using logistic regression. During testing, the model achieves high accuracy but low recall. How would you

Imagine you've built a predictive model for customer churn using logistic regression. During testing, the model achieves high accuracy but low recall. How would you interpret these results, and what implications would they have for the business? Discuss trade-offs between precision and recall

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