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

Authors:
Marcin Pluciński
Affiliations:
Faculty of Computer Science and Information Systems, West Pomeranian University of Technology, Szczecin, Poland
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Year:
2012

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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.