What is calibration in ensemble models?

Calibration ensures predicted probabilities reflect true likelihoods.

Many ensemble models like Random Forest and Boosting produce poorly calibrated probabilities. Calibration methods like Platt scaling or isotonic regression adjust predicted probabilities so they match observed frequencies. This is crucial in risk-sensitive applications like finance and healthcare.