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Special Invited Paper: Dimension Reduction and Visualization in Discriminant Analysis (with discussion)
Authors:R Dennis Cook  & Xiangrong Yin
Institution:Dept of Applied Statistics, University of Minnesota, USA,;Dept of Statistics, University of Georgia, USA
Abstract:This paper discusses visualization methods for discriminant analysis. It does not address numerical methods for classification per se, but rather focuses on graphical methods that can be viewed as pre-processors, aiding the analyst's understanding of the data and the choice of a final classifier. The methods are adaptations of recent results in dimension reduction for regression, including sliced inverse regression and sliced average variance estimation. A permutation test is suggested as a means of determining dimension, and examples are given throughout the discussion.
Keywords:central subspaces  dimension reduction  regression  regression graphics  sliced inverse regression (SIR)  sliced average variance estimation (SAVE)  
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