Calibration, Data Science, Machine Learning, Supervised Learning, Regression.
not guarantee an improvement in the existing model class accuracy, metrics like accuracy, precision, or recall also play an important role. The most common types of miscalibration are: l. Systematic overestimation. Compared to the true distribution, the distribution of predicted probabilities is