A Two-Dimensional Display for the Classification of Multivariate Data

Abstract

The properties of a two-dimensional display whose coordinates are the Euclidean distances from two points in a multivariate space are presented. When used in conjunction with three linear normalization procedures, this display is a useful tool in both supervised and unsupervised classification problems. In addition, some geometric structure is preserved by this mapping. Examples using well-known Iris data are presented to demonstrate the display characteristics.