Probability calibration aligns predicted probabilities with real-world outcomes, ensuring a model’s 70% confidence truly means 70% success. Used in risk scoring, forecasting, and medical diagnosis, it improves decision-making under uncertainty. Beneficiaries include data scientists, analysts, and anyone relying on trustworthy probabilistic predictions.
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