Data Science, Machine Learning, Statistics, Deep Dives, Probability.
Isotonic regression is better when we have enough data to prevent overfitting (Niculescu-Mizil and Caruana, 2005). Consider that calibration won’t automatically produce a well-calibrated model. The models whose predictions can be better calibrated are boosted trees, random forests, SVMs, bagged