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Sequential preprocessing through ORThogonalization (SPORT) and its application to near infrared spectroscopy

Abstract : In spectroscopy, multivariate calibrations more than often include a pre-processing step to reduce the effect of unwanted (not Y-related) sources of variability. Because there are many types of background noise, there are many pre-treatment methods. It is therefore tedious to select and/or combine the best pre-treatments. This article proposes to combine several pre-treatments through the use of sequential and orthogonalized partial least squares (SO-PLS), thus leading to a boosting method. The performances and properties of this new method, called Sequential Preprocessing through ORThogonalization (SPORT), are compared to those of a previously published stacking method. SPORT demonstrates very good calibration performances, but also the ability to make significant pretreatment selections.
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https://hal.inrae.fr/hal-02963019
Contributor : Isabelle Nault <>
Submitted on : Friday, October 9, 2020 - 4:24:18 PM
Last modification on : Wednesday, October 14, 2020 - 4:22:00 AM

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Jean-Michel Roger, Alessandra Biancolillo, Federico Marini. Sequential preprocessing through ORThogonalization (SPORT) and its application to near infrared spectroscopy. Chemometrics and Intelligent Laboratory Systems, Elsevier, 2020, 199, ⟨10.1016/j.chemolab.2020.103975⟩. ⟨hal-02963019⟩

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