Using evolutionary computation to solve problems in nonparametric regression

This paper studies evolutionary mechanism of parameter selection in the construction of weight function for Nearest Neighbour Estimate in nonparametric regression. Construct an algorithm which adaptively evolves fine weight and makes good prediction about unknown points. The numerical experiments indicate that this method is effective. It is a meaningful discussion about practicability of nonparametric regression and methodology of adaptive model-building. Supported by the National Natural Science Foundation and 863 High Technology Project of China Ding Lixin: born in 1967, Ph.D. graduate student