What is the concept of model calibration in probabilistic classifiers?

Question

Machine Learning — Medium

What is the concept of model calibration in probabilistic classifiers?

Accepted Answer

Model calibration in probabilistic classifiers refers to the alignment between predicted probabilities and actual outcomes. A well-calibrated model should predict 80% probability correctly around 80% of the time.