symbolic regression using nearest neighbor indexing
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.
symbolic regression genetic programming nearest neighbor search system identification feature selection