Abstract
Unlike regression analysis which uses algebraic functions for data fitting, neural networks uses a stepwise method called the steepest descent method for the purpose. This chapter is to asses whether typically nonlinear relationships can be adequately fit by this method.
This chapter was previously published in “Machine learning in medicine-cookbook 1” as Chap. 13, 2013.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Electronic Supplementary Material(s)
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Cleophas, T.J., Zwinderman, A.H. (2020). Neural Networks for Assessing Relationships that are Typically Nonlinear (90 Patients). In: Machine Learning in Medicine – A Complete Overview. Springer, Cham. https://doi.org/10.1007/978-3-030-33970-8_55
Download citation
DOI: https://doi.org/10.1007/978-3-030-33970-8_55
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33969-2
Online ISBN: 978-3-030-33970-8
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)