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Random correlation in variable selection for multivariate calibration with a genetic algorithm
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DOI：10.1016/S0169-7439(96)00062-7.png)
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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.
Keyword:
near-infrared spectroscopy
wavelength selection
genetic algorithm
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