Articles | Volume 6, issue 2
SOIL, 6, 565–578, 2020
https://doi.org/10.5194/soil-6-565-2020
SOIL, 6, 565–578, 2020
https://doi.org/10.5194/soil-6-565-2020
Original research article
17 Nov 2020
Original research article | 17 Nov 2020

The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data

Wartini Ng et al.

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Latest update: 06 Jul 2022
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Short summary
The number of samples utilised to create predictive models affected model performance. This research compares the number of samples needed by a deep learning model to outperform the traditional machine learning models using visible near-infrared spectroscopy data for soil properties predictions. The deep learning model was found to outperform machine learning models when the sample size was above 2000.