Spectral Feature Selection for Near-Infrared Spectroscopy Processing

Primarily applied for spectral feature selection in near-infrared spectroscopy processing, this method stands as one of the most significant approaches in current near-infrared spectral data analysis. The implementation typically involves dimensionality reduction algorithms and feature importance evaluation techniques to identify optimal wavelength ranges.