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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.
Clustering, dimensionality reduction, display mapping, iterative operation, multivariate data analysis, optimal decision boundaries, pattern recognition, supervised classification, unsupervised classification.

K. Fukunaga and D. Olsen, "A Two-Dimensional Display for the Classification of Multivariate Data," in IEEE Transactions on Computers, vol. 20, no. , pp. 917-923, 1971.
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