Forward feature selection on normalized full-spectrum transmission data with linear regression and 10-fold cross-validation reduces MSE for food-dye concentration from >22,000 to 3.87.
6 together present a comprehensive summary of the greedy forward feature selection process applied to normalized transmission data
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Multi-Wavelength Machine Learning for High-Precision Colorimetric Sensing
Forward feature selection on normalized full-spectrum transmission data with linear regression and 10-fold cross-validation reduces MSE for food-dye concentration from >22,000 to 3.87.