Title of article :
CovSel: Variable selection for highly multivariate and multi-response calibration: Application to IR spectroscopy
Author/Authors :
Roger ، نويسنده , , J.M. and Palagos، نويسنده , , B. and Bertrand، نويسنده , , D. and Fernandez-Ahumada، نويسنده , , E.، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2011
Abstract :
Variable selection is of major interest for NIR calibration, either as a feature selection or for the design of multi-wavelength devices. Some dedicated methods have been developed in chemometrics, but a few of them addresses explicitly the case of multi-response calibration. Variable selection for NIR spectroscopy must face two problems: (1) the huge number of variables yields a very large solution space; (2) variables are highly correlated, and if no special attention is paid the model built on the selection may be ill-conditioned. This article presents a new method, CovSel, which tackles these two problems by following this procedure: (1) variable selection step by step on the basis of their global covariance with all the responses; and (2) projection of the data orthogonally to the selected variable. CovSel was applied on three problems: the first one concerns a single response MIR calibration (Brix degree content in apricot), the second one concerns a multi-response NIR calibration (4 main constituents in corn) and the last application concerns the NIR discrimination of 3 wine grape varieties.
Keywords :
variable selection , Orthogonal projection
Journal title :
Chemometrics and Intelligent Laboratory Systems
Journal title :
Chemometrics and Intelligent Laboratory Systems