Can machine learning improve prediction – an application with farm survey data
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DOI: 10.22004/ag.econ.284919
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Cited by:
- Chen, Jian & Katchova, Ani L. & Zhou, Chenxi, 2021.
"Agricultural loan delinquency prediction using machine learning methods,"
International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(5), May.
- Chen, Jian & Katchova, Ani, 2019. "Agricultural Loan Delinquency Prediction Using Machine Learning Methods," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 290745, Agricultural and Applied Economics Association.
- Baaken, Dominik & Hess, Sebastian, 2021. "Forecasting Regional Milk Production Quantity: A Comparison of Regression Models and Machine Learning," 2021 Conference, August 17-31, 2021, Virtual 315117, International Association of Agricultural Economists.
- Baaken, Dominik & Hess, Sebastian, 2021. "Regionale Milchmengenprognose: Regressionsmodelle und Maschinelles Lernen im Vergleich," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317056, German Association of Agricultural Economists (GEWISOLA).
- Zhigui Guan & Yuanjun Zhao & Guojing Geng, 2022. "The Risk Early-Warning Model of Financial Operation in Family Farms Based on Back Propagation Neural Network Methods," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1221-1244, December.
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