Classification: Oldtimers and newcomers

This paper discusses the connection between these two methods and introduces two new ones of the same family: DASCO (discriminant analysis with shrunken covariances) and RDA (regularized discriminant analysis), demonstrating on both simulated and real data sets that their performance is superior to the old favorites.

Abstract

Abstract Classification and regression techniques are among the most used tools by chemometricians. With classification, the two classic methods are discriminant analysis and SIMCA. In this paper we discuss the connection between these two methods and introduce two new ones of the same family: DASCO (discriminant analysis with shrunken covariances) and RDA (regularized discriminant analysis). We demonstrate on both simulated and real data sets that their performance is superior to the old favorites. This is especially true in small‐sample/high‐dimension settings typical in chemistry.