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Mastering Predictive Analytics with R - Second Edition by Rui Miguel Forte, James D. Miller

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Radial basis function networks

A radial basis function network-based upon the concept of function approximation - is a kind of artificial neural network that uses radial basis functions to define a node's output (given a set of inputs). The output of the network consists of a linear combination of radial basis functions of the inputs and neuron parameters.

Radial basis function (RBF) networks (also referred to as RBFNN for Radial Basis Function Neural Networks) will have three separate layers: an input layer, a hidden layer, and a linear output layer. The input layer will be a set of several nodes that transfer transition the input values to the second (or hidden) layer where activation patterns are applied. These patterns will be selected radial ...

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