Exploring feature extraction methods for Raman spectroscopy: A comparative study

For the first time, this study provides a systematic and in-depth examination of the reduced feature spaces generated by each method, offering a comprehensive understanding of their structural properties, interpretability, and impact on classification performance. The results highlight MCR as a particularly promising method for feature extraction in Raman spectroscopy. Its ability to produce chemically interpretable features and incorporate physicochemical constraints offers a key advantage over conventional techniques such as PCA. These characteristics make MCR especially suitable for analyzing complex Raman spectral data, where both classification accuracy and interpretability are crucial.