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In this paper, we introduce a new nearest neighbor data structure and describe several ways that it may be used for symbolic regression. Compared to genetic programming alone an algorithm using nearest neighbor indexing can search a much larger space and even so, typically find smaller, more general models. In addition, we introduce permutation tests in order to discriminate between relevant and irrelevant features.