## Calibration for deep learning models

Wikipedia’s definition for calibration is calibration is the comparison of measurement values delivered by a device under test with those of a calibration standard of known accuracy. Put in a context that means that the distribution of predicted probabilities is similar to the distribution observed probabilities in training data. If we rephrase it again means that if your model is predicting cat vs dog and the model states that a given image is a cat with 70% probability then theRead More→