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Breaking with trends in pre-processing?

2013; Elsevier BV; Volume: 50; Linguagem: Inglês

10.1016/j.trac.2013.04.015

1879-3142

Jasper Engel, Jan Gerretzen, Ewa Szymańska, Jeroen J. Jansen, Gérard Downey, Lionel Blanchet, L.M.C. Buydens,

Advanced Chemical Sensor Technologies

Data pre-processing is an essential part of chemometric data analysis, which aims to remove unwanted variation (such as instrumental artifacts) and thereby focusing on the variation of interest. The choice of an optimal pre-processing method or combination of methods may strongly influence the analysis results, but is far from straightforward, since it depends on the characteristics of the data set and the goal of data analysis. This first critical review is devoted to the selection procedure for appropriate pre-processing strategies. We show that breaking with current trends in pre-processing is essential, as all selection approaches have serious drawbacks and cannot be properly used.