Optimizing feature selection with gradient boosting machines in PLS regression for predicting moisture and protein in multi-country corn kernels via NIR spectroscopy

Zheng, Runyu; Jia, Yuyao; Ullagaddi, Chidanand; Allen, Cody; Rausch, Kent; Singh, Vijay; Schnable, James C.; Kamruzzaman, Mohammed

doi:10.1016/j.foodchem.2024.140062

Food Chemistry

2024

DOI: 10.1016/j.foodchem.2024.140062

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Optimizing feature selection with gradient boosting machines in PLS regression for predicting moisture and protein in multi-country corn kernels via NIR spectroscopy

Runyu Zheng,

Yuyao Jia,

Chidanand Ullagaddi

et al.

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Optimizing feature selection with gradient boosting machines in PLS regression for predicting moisture and protein in multi-country corn kernels via NIR spectroscopy

Cited by 5 publications

References 47 publications

Single-nucleus sequencing unveils heterogeneity in renal cell carcinomas microenvironment: Insights into pathogenic origins and treatment-responsive cellular subgroups

Single-nucleus sequencing unveils heterogeneity in renal cell carcinomas microenvironment: Insights into pathogenic origins and treatment-responsive cellular subgroups

Non-targeted metabolomics and explainable artificial intelligence: Effects of processing and color on coniferyl aldehyde levels in Eucommiae cortex

Near-infrared spectroscopy combined with support vector machine for the identification of Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn) adulteration using wavelength selection algorithms

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