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Boosting partial least squares (PLS) has been used for regression to improve the predictive accuracy of PLS models, however, there are still problems when the outliers exist in the calibration dataset. To make the method robust and enhance its prediction ability, an improved boosting PLS is proposed and applied in quantitative analysis of near-infrared (NIR) spectral datasets. In the method, a robust...
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