Abstract
The first chapter of this thesis introduces Function Approximation (FA), also called regression, which is the basic feature required to learn sensorimotor mappings. A multitude of algorithm classes are introduced, including simple model fitting, interpolation, and advanced concepts such as Gaussian Processes and Artificial Neural Networks. The last section of this chapter discusses the applicability, but also questions the plausibility of such algorithms in the light of brain functionality.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 Springer Fachmedien Wiesbaden
About this chapter
Cite this chapter
Stalph, P. (2014). Introduction to Function Approximation and Regression. In: Analysis and Design of Machine Learning Techniques. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-04937-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-658-04937-9_2
Published:
Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-04936-2
Online ISBN: 978-3-658-04937-9
eBook Packages: EngineeringEngineering (R0)