RADIAL BASIS FUNCTIONS FOR EXPLORATORY DATA-ANALYSIS - AN ITERATIVE MAJORISATION APPROACH FOR MINKOWSKI DISTANCES BASED ON MULTIDIMENSIONAL-SCALING

This paper considers the use of radial basis functions for exploratory data analysis. These are used to model a transformation from a high-d imensional observation space to a low-dimensional one. The parameters of the model are determined by optimising a loss function defined to b e the stress function in multidimensional scaling. The metric for the low-dimensional space is taken to be the Minkowski metric with order p arameter 1 less than or equal to p less than or equal to 2. A scheme b ased on iterative majorisation is proposed.