期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 106, 期 2, 页码 216-223出版社
ELSEVIER
DOI: 10.1016/j.chemolab.2010.10.003
关键词
Variable selection; Orthogonal projection
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. (C) 2010 Elsevier B.V. All rights reserved.
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