Quote:
Originally Posted by magdon
This is because there is some "best" and for any N, the final output g will be "scattered" around this , sometimes predicting above on a particular x and sometimes below, on average giving the prediction of . This results in being approximately for any N.

Thank you very much, Prof. MagdonIsmail, for the clarification, pointers, and encouragement!
Just one more question: in the quote above, when you said "there's some best
", did you mean the best
in current hypothesis set
for the current error measure,
independent of N? For example, if
consists of linear models and the error measure is mean squared error, then
would be the LMMSE estimate? Thanks a lot!