A logistic regression model for customer churn gives these standardized coefficients:Feature Coefficient Odds Ratio contract_monthly 1.2 3.32 monthly_charges 0.8 2.23 tenure -0.9 0.41 tech_support -0.3 0.74Interpret the odds ratio for ‘tenure’ — what does 0.41 mean in business terms? Which feature has the strongest effect on churn, and how do you know?
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An odds ratio of 0.5 for a feature means:
An odds ratio of 0.5 for a feature means:
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What does a False Negative (FN) mean in a churn prediction model?
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