Feature Variable Extraction Using Competitive Adaptive Reweighting Sampling (CARS) Method

A MATLAB-based feature variable extraction method for pattern recognition (classification and regression), Competitive Adaptive Reweighting Sampling (CARS) employs Adaptive Reweighted Sampling (ARS) technology to select wavelength points with large absolute regression coefficients in PLS models while eliminating low-weight wavelength points. The method utilizes cross-validation to identify subsets with the lowest RMSECV values, effectively determining optimal variable combinations. Implementation typically involves iterative weight updates and Monte Carlo sampling techniques for robust feature selection.