Logistic regression predicts binary outcomes, like yes/no or pass/fail, by modeling probabilities through a sigmoid curve. It’s widely used in healthcare for disease diagnosis, marketing for customer churn, and finance for credit risk. Data scientists, analysts, and researchers benefit from its interpretability and efficiency with small datasets.
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