The effect of preprocessing methods in reducing interfering variability from near-infrared measurements of creams

Variables selection methods in near-infrared spectroscopy

“…Wu et al used Kalman filtering [34], Fisher's weights [33,35,103] and Bayesian [104] as a feature selection method. Kalman filtering, Fisher's weights and Bayesian are the classical statistic methods.…”

Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging

“…In this study, MSC was applied for spectral pre-processing as it performs well in correcting light scattering variation and multiplicative noise arising from the physical structure of samples (Luypaert, Heuerding, Heyden, & Massart, 2004).…”

Near infrared and Raman spectroscopy for the in-process monitoring of pharmaceutical production processes

“…Spectral pretreatment before chemometric analysis is often desired to reduce the effect of 266 interfering variance in which one is not interested, thereby increasing the part of the variance due to 267 parameters of interest (Luypaert et al, 2004). Adequate spectral preprocessing is hence very critical 268 for further chemometric data-analysis and data-interpretation (Rinnan, 2009).…”