Determining the optimal number of folds to use in a K-fold cross-validation: A neural network classification experiment

Opeoluwa Oyedelea Department of Computing, Mathematical and Statistical Sciences, School of Science, University of Namibia, Windhoek, NamibiaCorrespondence[email protected]

https://orcid.org/0000-0002-3053-0702 View further author information

Hemen Duttab Gauhati University, INDIAView further author information

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Hyerin Kim, Sungmin Jeong, Jieun Kwak & Suyong Lee. (2023) Artificial intelligence classification and amylose content prediction of rice flour varieties from their pasting features. Journal of Agriculture and Food Research 14, pages 100847.
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Determining the optimal number of folds to use in a K-fold cross-validation: A neural network classification experiment

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Determining the optimal number of folds to use in a K-fold cross-validation: A neural network classification experiment

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