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Mean Squared Error
Mean Squared Error

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!!! Overview
[{$pagename}] ([MSE])
!! [{$pagename}] [Loss function]
[{$pagename}], or sometimes called L2 Loss, is the most common [Loss function] in [Machine Learning]
If YHat is a [vector] of n predictions, and Y is the [vector] of observed values of the variable being predicted, then the within-sample [MSE] of the predictor is computed as
[Mean Squared Error/Screen Shot 2017-12-26 at 05.56.09.png]
!! Category
%%category [Artificial Intelligence]%%
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop