Multidimensional scaling by iterative majorization using radial basis functions

Abstract This paper considers the use of radial basis functions for modelling the non-linear transformation of a data set obtained by a multidimensional scaling analysis. This approach has two advantages over conventional nonmetric multidimensional scaling. It reduces the number of parameters to estimate and it provides a transformation that may be used on an unseen test set. A scheme based on iterative majorization is proposed for obtaining the parameters of the network.

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