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.
Review of the most common pre-processing techniques for near-infrared spectra
2 Pith papers cite this work. Polarity classification is still indexing.
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BISN achieves 0.93 mean leave-one-batch-out accuracy on 2700 NIR spectra from three insect species across three batches, outperforming baselines by 4% while decisions align with lipid and protein absorption regions.
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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.
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Batch-Invariant Spectral Intelligence for Robust and Explainable Insect Authentication
BISN achieves 0.93 mean leave-one-batch-out accuracy on 2700 NIR spectra from three insect species across three batches, outperforming baselines by 4% while decisions align with lipid and protein absorption regions.