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Old 05-25-2017, 11:20 PM
Steve_Y Steve_Y is offline
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Join Date: May 2017
Posts: 2
Default Re: bias-variance plot on p67

Originally Posted by magdon View Post
This is because there is some "best" h^* and for any N, the final output g will be "scattered" around this h^*, sometimes predicting above h^* on a particular x and sometimes below, on average giving the prediction of h^*. This results in \bar g being approximately h^* for any N.
Thank you very much, Prof. Magdon-Ismail, for the clarification, pointers, and encouragement!

Just one more question: in the quote above, when you said "there's some best h^*", did you mean the best h^* in current hypothesis set \cal H for the current error measure, independent of N? For example, if \cal H consists of linear models and the error measure is mean squared error, then h^* would be the LMMSE estimate? Thanks a lot!
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