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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 8, Iss. 8 — Sep. 4, 2013

Weighted Fusion of Multiple Models for Wavelength Selection

Tianling Zeng, Zhiyu Wen, Zhongquan Wen, and Mingjian Hong

Applied Spectroscopy, Vol. 67, Issue 7, pp. 718-723 (2013)


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Abstract

A new method based on the weighted fusion of multiple models is presented for wavelength selection in multivariate calibration of spectral data. It fuses the regression coefficients of multiple models with weights based on minimum mean square error to improve the accuracy and stability of the wavelength selection. To validate the performance of the proposed method, it was applied to the partial least squares (PLS) modeling of three near-infrared spectral datasets and compared with full-spectrum PLS, genetic algorithm-based PLS, and uninformative variable elimination-based PLS methods. Results show that the proposed method can effectively select the informative wavelength and enhance the prediction ability of the PLS model. On account of its simpler algorithm and higher efficiency, it can be widely used in practical applications.

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Vol. 8, Iss. 8 Virtual Journal for Biomedical Optics

Citation
Tianling Zeng, Zhiyu Wen, Zhongquan Wen, and Mingjian Hong, "Weighted Fusion of Multiple Models for Wavelength Selection," Appl. Spectrosc. 67, 718-723 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=as-67-7-718

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