Learning and generalization in radial basis function networks

The aim of supervised learning is to approximate an unknown target function by adjusting the parameters of a learning model in response to possibly noisy examples generated by the target function. The performance of the learning model at this task can be quantified by examining its generalization ab...

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Bibliographic Details
Main Author: Freeman, Jason Alexis Sebastian
Published: University of Edinburgh 1998
Subjects:
Online Access:https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.651126