Regularisation in the Selection of Radial Basis Function Centres
نویسنده
چکیده
Subset selection and regularisation are two well known techniques which can improve the generalisation performance of nonparametric linear regression estimators, such as radial basis function networks. This paper examines regularised forward selection (RFS) { a combination of forward subset selection and zero-order regularisation. An eecient implementation of RFS into which either delete-1 or generalised cross-validation can be incorporated and a re-estimation formula for the regularisation parameter are also discussed. Simulation studies are presented which demonstrate improved generalisation performance due to regularisation in the forward selection of radial basis function centres.
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تاریخ انتشار 1995