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If I were expressing a problem in terms of binary features, all encoded as {0,1}, could I boost some features by encoding them as {0,2}? Would the effect change based on whether I used either of the approaches above (logistic regression or linear SVMs?) Any paper recommendations that would explain the mathematics?

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No, those are linear methods, the results would be equivalent. Multiplying $x$ by two would be offset by halfing the coefficient estimate.

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  • $\begingroup$ i guess you’d need to tweak the optimization algorithm (e.g. gradient descent) to favor some of the parameters over others? $\endgroup$ – Walrus the Cat Jun 29 '19 at 21:16

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