A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data

• Published in: International journal of analytical chemistry Vol. 2019; no. 2019; pp. 1 - 12
• Main Authors: Yi, Lun-Zhao, Wang, Feng-Hua, Zong, Min-Jie, Fu, Guang-Hui
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 2019; Hindawi; John Wiley & Sons, Inc; Wiley
• Subjects: Algorithms; Analytical chemistry; Bioinformatics; Calibration; Computer simulation; Economic models; Infrared analysis; Infrared spectroscopy; Laboratories; Least squares; Model accuracy; Near infrared radiation; Regression analysis; Sparsity; Spectrum analysis; Wavelengths

Elastic net (Enet) and sparse partial least squares (SPLS) are frequently employed for wavelength selection and model calibration in analysis of near infrared spectroscopy data. Enet and SPLS can perform variable selection and model calibration simultaneously. And they also tend to select wavelength...