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We introduce a new version of forward stepwise regression. Our modificationfinds solutions to regression problems where the selected predictors appear ina structured pattern, with respect to a predefined distance measure over thecandidate predictors. Our method is motivated by the problem of predictingHIV-1 drug resistance from protein sequences. We find that our method improvesthe interpretability of drug resistance while producing comparable predictiveaccuracy to standard methods. We also demonstrate our method in a simulationstudy and present some theoretical results and connections.

Structured, sparse regression with application to HIV drug resistance