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Random correlation in variable selection for multivariate calibration with a genetic algorithm

✍ Scribed by D. Jouan-Rimbaud; D.L. Massart; O.E. de Noord

Publisher: Elsevier Science
Year: 1996
Tongue: English
Weight: 549 KB
Volume: 35
Category: Article
ISSN: 0169-7439
DOI: 10.1016/s0169-7439(96)00062-7

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✦ Synopsis

The importance of the validation step in multiple linear regression of near-infrared spectroscopic data, after selection of wavelengths by a genetic algorithm, is investigated with the use of random variables. It is shown that in spite of a careful validation procedure, the GA can still select irrelevant variables. The effect is greatly reduced by applying a forward selection in the subsets selected by the genetic algorithm.

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