Biplot Methodology for Discriminant Analysis Based upon Robust Methods and Principal Curves
Biplots not only are useful graphical representations of multidimensional data,but formulating discriminant analysis in terms of biplot methodology can lead to several novel extensions. In this paper it is shown that incorporating both principal curves and robust canonical variate analysis algorithms in biplot methodology often leads to superior classification.
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- GARDNER, S. (2001): Extensions of biplot methodology to discriminant analysis with applications of non-parametric principal components. Unpublished PhD thesis, University of Stellenbosch.Google Scholar
- GOWER, J.C. (1995): A general theory of biplots. In: W.J. Krzanowski. (ed.): Recent advances in descriptive multivariate analysis. Clarendon Press, Oxford, 283–303.Google Scholar
- MCLACHLAN, G.J. (1992): Discriminant analysis and statistical pattern recognition. John Wiley, New York.Google Scholar