Combination of heuristic optimal partner bands for variable selection in near‐infrared spectral analysis

Journal of Chemometrics - Tập 32 Số 11 - 2018
Jin Zhang1, Xiaoyu Cui1, Wensheng Cai1, Xueguang Shao2,1,3,4,5
1Research Center for Analytical Sciences, College of Chemistry, Nankai University, Tianjin 300071, China
2Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300071, China
3State Key Laboratory of Medicinal Chemical Biology, Tianjin 300071, China
4Tianjin Key Laboratory of Biosensing and Molecular Recognition, Tianjin 300071, China
5Xinjiang Laboratory of Native Medicinal and Edible Plant Resources Chemistry, College of Chemistry and Environmental Science, Kashgar University, Kashgar 844006, China

Tóm tắt

AbstractVariable selection plays a critical role in the analysis of near‐infrared (NIR) spectra. A method for variable selection based on the principle of the successive projection algorithm (SPA) and optimal partner wavelength combination (OPWC) was proposed for NIR spectral analysis. The method determines a number of knot variables with sufficient independence by SPA, and candidate variable bands with a definite width are defined. The cooperative effect of the bands is then evaluated with the partial least squares regression model by using the method of OPWC. The performance of the proposed method was compared with those of SPA, OPWC, randomization test, competitive adaptive reweighted sampling, and Monte Carlo uninformative variable elimination by using NIR datasets for pharmaceutical tablets, corn, and soil. The results show that the proposed method can select informative variable bands with a cooperative effect and improves the model for quantitative analysis.

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Journal of Chemometrics

Tập 32 Số 11

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