Spectrophotometric variable selection by mutual information

Spectrophotometric data often comprise a great number of numerical components or variables that can be used in calibration models. When a large number of such variables are incorporated into a particular model, many difficulties arise, and it is often necessary to reduce the number of spectral varia...

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Bibliographic Details
Published in:Chemometrics and intelligent laboratory systems 2004-12, Vol.74 (2), p.243-251
Main Authors: Benoudjit, N., François, D., Meurens, M., Verleysen, M.
Format: Article
Language:English
Subjects:
Mutual information
Spectrophotometric variable selection
Spectrophotometry
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Summary:Spectrophotometric data often comprise a great number of numerical components or variables that can be used in calibration models. When a large number of such variables are incorporated into a particular model, many difficulties arise, and it is often necessary to reduce the number of spectral variables. This paper proposes an incremental (Forward–Backward) procedure, initiated using an entropy-based criterion (mutual information), to choose the first variable. The advantages of the method are discussed; results in quantitative chemical analysis by spectrophotometry show the improvements obtained with respect to traditional and nonlinear calibration models.
ISSN:0169-7439
1873-3239
DOI:10.1016/j.chemolab.2004.04.015