Operator-adaptive PLS and Ridge models integrate linear preprocessing screening internally via algebraic identities, delivering comparable or better prediction accuracy than exhaustive external search on NIR regression and classification tasks with orders-of-magnitude lower fitting time.
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Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models
Operator-adaptive PLS and Ridge models integrate linear preprocessing screening internally via algebraic identities, delivering comparable or better prediction accuracy than exhaustive external search on NIR regression and classification tasks with orders-of-magnitude lower fitting time.