Calibration, Data Science, Machine Learning, Supervised Learning, Regression.
Sense? That's why we need calibration of our probability scores. The idea of probability calibration is to build a second model (called calibrator) that is able to correct them into actual probabilities. Calibration consists of a function that transforms a -1 dimensional vector (uncalibrated