What is the difference between sigma^2 and MSE in the
I would've thought that they would be the same, thinking that:
- MSE = The mean of the squared errors, where errors = the differences between the training data and the values fitted by the model produced from said training data.
- sigma^2 = The same.
My guess is that it is something along the lines of sigma^2 being under a transformation.