Re: Linear regression with constraint on the hypothesis set
Thank you, sir, I think I finally got it. So if I want to pin down a number of M weights, I just move the constant M terms to the y vector (subtracting from it), and I am left with a matrix X with d+1-M columns (the column of ones may also be gone). The result will be a vector of d+1-M weights.
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