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Selection of discriminant wavelength intervals in NIR spectrometry with genetic algorithms
Author(s) -
Reynès Christelle,
Souza Sabrina de,
Sabatier Robert,
Figuères Gilles,
Vidal Bernard
Publication year - 2006
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1000
Subject(s) - linear discriminant analysis , discriminant , context (archaeology) , feature selection , selection (genetic algorithm) , pattern recognition (psychology) , genetic algorithm , factorial , feature (linguistics) , computer science , artificial intelligence , algorithm , mathematics , machine learning , biology , paleontology , mathematical analysis , linguistics , philosophy
Spectra, obtained in visible and near infrared spectral regions, contain much information whose interest depends on the context. For instance, in a discrimination context, the only information of interest is the one, concerning the differences between groups. This is our problem and we want to determine zones in the spectra (intervals), allowing a good discrimination between groups defined in advance. In that goal, genetic algorithms (GAs) will be used as a method of feature (wavelengths) selection. The Fisher Linear Discriminant Analysis (or Factorial Discriminant Analysis denoted FDA) will be applied on the selected variables. The efficiency of the method is shown on the discrimination of tobacco products. Copyright © 2007 John Wiley & Sons, Ltd.