no. 3
Joint selection of wavenumber regions for MidIR and RAMAN spectra and variables in PLS regression using Genetic Algorithms
[Sélection conjointe de régions de spectres MidIR et RAMAN et de variables en régression PLS à l’aide d’Algorithmes Génétiques]
Journal de la société française de statistique, Tome 154 (2013) no. 3, pp. 80-94.

De nombreuses méthodes adaptées pour la régression PLS, s’intéressent aux choix de variables explicatives, quand celles-ci sont en nombre trop important. Quand il s’agit de sélectionner des intervalles pour des spectres, la panoplie des techniques est plus réduite. Dans ce travail, PLS a été associée aux algorithmes génétiques pour permettre la sélection d’intervalles dans des spectres. L’origine de ce travail est une problématique de régression pour des données sur la transformation de manioc. Ces données sont constituées de trois tableaux : des spectres RAMAN, MidIR et des variables physico-chimiques. Il s’agit d’adapter au contexte de régression une stratégie précédemment mise au point pour la sélection d’intervalles uniquement pour des spectres NIR en discrimination. Nous avons développé un algorithme génétique spécialement adapté à ce type de données (multitableau), pour le cas de la régression PLS1. Des illustrations sur des données simulées sont proposées avant l’application au jeu de données réel.

Many methods exist for feature selection in PLS regression when there are too many variables. Less methods are available for selecting wavenumber regions for MidIR or RAMAN spectra. In this work, PLS has been coupled with genetic algorithms to allow for the selection of intervals in spectra. This work was motivated by a regression issue about transformation of cassava. Those data consist of three tables: RAMAN spectra, MidIR spectra and physico-chemical variables. The purpose is to adapt to this regression context a strategy previously designed to select intervals in NIR spectra in classification. A new algorithm is proposed to fit such multiblock data in PLS1 regression context. Illustrations on simulated data are performed before application to the real dataset.

Keywords: PLS Regression, Genetic Algorithm, MidIR and RAMAN spectra, Variable Selection, Selection of wavenumber regions
Mot clés : Méthode PLS, Algorithme Génétique, Spectres MidIR et RAMAN, Choix de variables, Sélection d’intervalles 
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Grosmaire, Lidwine; Reynès, Christelle; Sabatier, Robert. Joint selection of wavenumber regions for MidIR and RAMAN spectra and variables in PLS regression using Genetic Algorithms. Journal de la société française de statistique, Tome 154 (2013) no. 3, pp. 80-94. http://www.numdam.org/item/JSFS_2013__154_3_80_0/

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