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Comparative Analysis of Machine Learning Models for Predicting Rice Yield: Insights from Agricultural Inputs and Practices in Rwanda

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  • Cyprien Mugemangango, Joseph Nzabanita, Dieudonne Ndaruhuye Muhoza, Nathan Cahill

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  • Cyprien Mugemangango, Joseph Nzabanita, Dieudonne Ndaruhuye Muhoza, Nathan Cahill, 2024. "Comparative Analysis of Machine Learning Models for Predicting Rice Yield: Insights from Agricultural Inputs and Practices in Rwanda," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 5(4), November.
    • Handle: RePEc:ags:reowae:348769
    DOI: 10.22004/ag.econ.348769
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    as
    1. Anurag Satpathi & Parul Setiya & Bappa Das & Ajeet Singh Nain & Prakash Kumar Jha & Surendra Singh & Shikha Singh, 2023. "Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India," Sustainability, MDPI, vol. 15(3), pages 1-18, February.
    2. Jig Han Jeong & Jonathan P Resop & Nathaniel D Mueller & David H Fleisher & Kyungdahm Yun & Ethan E Butler & Dennis J Timlin & Kyo-Moon Shim & James S Gerber & Vangimalla R Reddy & Soo-Hyung Kim, 2016. "Random Forests for Global and Regional Crop Yield Predictions," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, June.
    3. Martin Kuradusenge & Eric Hitimana & Damien Hanyurwimfura & Placide Rukundo & Kambombo Mtonga & Angelique Mukasine & Claudette Uwitonze & Jackson Ngabonziza & Angelique Uwamahoro, 2023. "Crop Yield Prediction Using Machine Learning Models: Case of Irish Potato and Maize," Agriculture, MDPI, vol. 13(1), pages 1-19, January.
    4. Cor-Jacques Kat & Pieter Schalk Els, 2012. "Validation metric based on relative error," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 18(5), pages 487-520, January.
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