Mini-models - Local regression models for the function approximation learning

Abstract

Mini-models are local regression models which can be used for the function approximation learning. In the paper, there are presented mini-models based on hyper-spheres and researches were made for linear and nonlinear models with no limitations for the problem input space dimension. Learning of the approximation function based on mini-models is very fast and it proved to have a good accuracy. Mini-models have also very advantageous extrapolation properties. It results from a fact, that they take into account not only samples target values, but also a tendency in the neighbourhood of the question point. © 2012 Springer-Verlag Berlin Heidelberg.