CARS-PLS MATLAB Source Code for Variable Selection in Spectroscopic or Chromatographic Data

CARS-PLS is a MATLAB-based source code package designed for variable selection in spectroscopic or chromatographic data analysis. The implementation incorporates multiple algorithms including Competitive Adaptive Reweighted Sampling (CARS) and Partial Least Squares (PLS) to analyze datasets and identify the most representative and relevant variables. The CARS algorithm works by iteratively selecting informative variables through adaptive reweighted sampling, while PLS handles the regression modeling between selected variables and response data. The code provides built-in visualization tools that generate plots showing variable importance, selection frequency, and model performance metrics, enabling users to intuitively understand data characteristics and patterns. Key functions include data preprocessing, cross-validation, model optimization, and results visualization. Using CARS-PLS for data analysis not only improves analytical efficiency but also provides deeper insights into data patterns, offering stronger support for data processing and decision-making workflows. The code structure follows modular design principles, allowing easy customization and integration with existing MATLAB analytical pipelines.