You want to predict rental prices of apartments in a big city using their location, size, amenities, and other features. You have access to data on many apartments with many variables. You know how to select the best regression model for prediction from several candidate models. But how should you specify those candidate models to begin with? In particular, which of the many variables should they include, in what functional forms, and in what interactions? More generally, how can you make sure that the candidates include the truly good predictive models?
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