I came across a new term called Calibration
while reading about prediction models.
Can you please help me understand how different it is from Discrimination
.
We build ML models to discriminate two/more classes from one another
But what does calibration
mean and what does it mean to say that "The model has good discriminative power but poorly calibrated/calibrative power`?"
I thought we usually only look for separation only between 2 classes.
Can help me with this with a simple example please?