Optimal projections of high dimensional data

Abstract

In this paper, we compare two artificial neural network algorithms for performing Exploratory Projection Pursuit, a statistical technique for investigating data by projecting it onto lower dimensional manifolds. The neural networks are extensions of a network which performs Principal Component Analysis. We illustrate the technique on artificial data before applying it to real data.