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Classification and regression techniques are among the most used tools by chemometricians.Withclassification,the two classic methods are discriminant analysis and SIMCA.In this paper we discuss theconnection between these two methods and introduce two new ones of the same family:DASCO(discriminantanalysis with shrunken covariances)and RDA(regularized discriminant analysis).We demonstrate on bothsimulated and real data sets that their performance is superior to the old favorites.This is especially truein small-sample/high-dimension settings typical in chemistry. 相似文献
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