Development of automatic tuning for combined preprocessing and hyperparameters of machine learning and its application to NIR spectral data of coconut milk adulteration
Author:
Funder
King Mongkut's Institute of Technology Ladkrabang
Publisher
Elsevier BV
Reference39 articles.
1. Machine Learning–Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data;Ali;AAPS PharmSciTech,2023
2. Chemical composition and potential adulterants in coconut milk sold in Kuala Lumpur;Azlin-hashim;Malaysian Applied Biology,2019
3. Prediction of maize flour adulteration in chickpea flour (besan) using near infrared spectroscopy;Bala;Journal of Food Science and Technology,2022
4. Principles and applications of miniaturized near-infrared (NIR) spectrometers. Chemistry – A;Beć;European Journal,2021
5. A selective ensemble preprocessing strategy for near-infrared spectral quantitative analysis of complex samples;Bian;Chemometrics and Intelligent Laboratory Systems,2020
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