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Originally Posted by tsweetser
Is it also possible to use the regularized normal equation? I'm looking at Lecture 12, Slide 11.
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Yes, you can use any result given in the lectures.
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It seems funny to me to choose the parameters to minimize one error measure (mean square), yet evaluate {E_in} and {E_out} using another (binary classification).
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Ideally, we would work exclusively with binary classification error in this case, but because of the intractability of optimization of that error, the mean-squared error is used for the optimization part.