Machine learning-enhanced evaluation of food security across 169 economies
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10668-024-05212-1.pdf
Reference63 articles.
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3. Aslam, B., Zafar, A., & Khalil, U. (2022). Comparison of multiple conventional and unconventional machine learning models for landslide susceptibility mapping of Northern part of Pakistan. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-022-02314-6
4. Awad, M., & Khanna, R. (2015). Support vector regression. In Efficient learning machines. Springer, pp. 67–80.
5. Bajpai, D., & He, L. (2020). Evaluating KNN performance on WESAD dataset. In 12th International conference on computational intelligence and communication networks (CICN).
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