期刊
ANALYTICA CHIMICA ACTA
卷 858, 期 -, 页码 16-23出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2014.12.033
关键词
Consensus model; Variable selection; Successive projections algorithm; Near infrared spectra; Multiple linear regression
资金
- Zhejiang Provincial Natural Science Foundation of China [R1110261]
- [31201355]
- [61272018]
- [61303113]
The successive projections algorithm (SPA) is widely used to select variables for multiple linear regression (MLR) modeling. However, SPA used only once may not obtain all the useful information of the full spectra, because the number of selected variables cannot exceed the number of calibration samples in the SPA algorithm. Therefore, the SPA-MLR method risks the loss of useful information. To make a full use of the useful information in the spectra, a new method named consensus SPA-MLR (C-SPA-MLR) is proposed herein. This method is the combination of consensus strategy and SPA-MLR method. In the C-SPA-MLR method, SPA-MLR is used to construct member models with different subsets of variables, which are selected from the remaining variables iteratively. A consensus prediction is obtained by combining the predictions of the member models. The proposed method is evaluated by analyzing the near infrared (NIR) spectra of corn and diesel. The results of C-SPA-MLR method showed a better prediction performance compared with the SPA-MLR and full-spectra PLS methods. Moreover, these results could serve as a reference for combination the consensus strategy and other variable selection methods when analyzing NIR spectra and other spectroscopic techniques. (C) 2014 Elsevier B.V. All rights reserved.
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