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The table of contents for Chapter 5 is as follows
5.1 Introduction
5.2 Function Approximation
5.3 Choices for the
Elementary Functions
5.4 Probabilistic
Interpretation of the Mappings: Nonlinear Regression
5.5 Training Neural
Networks for Function Approximation
5.6 How to Select the
Number of Bases
5.7 Applications of Radial
Basis Functions
5.8 Support Vector Machines
5.9 Project: Applications
of Neural Networks as Function Approximators
5.10 Conclusion
5.11 Exercises
5.12 NeuroSolutions
Examples
5.13 Concept Map for
Chapter 5
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