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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University of Edinburgh
1998
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Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.651126 |