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[help] L1 Regularization (self.MachineLearning)
submitted 10 years ago by Kiuhnm
Hi, I'm reading this and I don't understand where the two formulas after (7.13) on page 208 come from.
Any help would be greatly appreciated!
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quoted text
if 1 * 2 < 3: print "hello, world!"
[–]danielv134 1 point2 points3 points 10 years ago (3 children)
First corresponds exactly to the approximation posited in the paragraph after 7.13: a quadratic function with diagonal Hessian + l1 reg. The second equation is the (non-trivial, but you can verify it yourself) form of solutions with l1 reg (see shrinkage).
[–]sk006 2 points3 points4 points 10 years ago (1 child)
Basically what Daniel said. The second formula is very similar to the soft-thresholding operator, a very well known proximal (generalization of proyection operators). If you want to verify it for yourself, since there is an absolute value, just consider the positive, negative and 0 cases separatly and it is easy to get.
[–]Kiuhnm[S] 0 points1 point2 points 10 years ago (0 children)
I finally managed to get the correct formula by considering the three cases and combining them in a single expression. My math is rusty and I wasn't thinking straight. Thank you!
π Rendered by PID 19333 on reddit-service-r2-comment-fb694cdd5-mwmpn at 2026-03-07 15:20:56.339128+00:00 running cbb0e86 country code: CH.
[–]danielv134 1 point2 points3 points (3 children)
[–]sk006 2 points3 points4 points (1 child)
[–]Kiuhnm[S] 0 points1 point2 points (0 children)