Machine Learning-based Milk Quality Prediction
Main Article Content
Keywords
milk, food quality, multilayer perceptron, XGBoost, SVM, logistic regression
Abstract
With improvements in people's living standards, food safety has gradually received increasing attention. Milk quality is an important aspect of food safety. By classifying quality, we can obtain milk of different grades for consumers to choose from. This report applies the MLP, logistic regression, SVM and XGBoost algorithms to determine a suitable model through comparison and decision-making.
References
- Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, California, USA. Association for Computing Machinery, pp. 785–794.
- Das, A., (2023). Logistic Regression. In: Maggino, F. (ed.) Encyclopedia of Quality of Life and Well-Being Research. Cham: Springer International Publishing, pp. 3985-3986.
- Ding, S. F., Qi, B. J. and Tan, H. Y., (2011). An overview on theory and algorithm of support vector machines. Journal of University of Electronic Science and Technology of China, vol. 40, no. 1, pp. 1-10.
Article Sidebar
Published
Dec 16, 2025
Conference Proceedings Volume
Section
Articles
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Zhao, Bojun. “Machine Learning-Based Milk Quality Prediction”. Exploring Science Academic Conference Series, vol. 9, Dec. 2025, pp. 1-14, https://doi.org/10.70267/ic-aimees.202501.