摘要
传统的农业政策分析偏重于分析变量之间关系和模型参数的估计,而"机器学习"更注重对未来结果预测的准确性,而后者恰恰是农业政策分析的目的。"机器学习"具有庞大的数据收集和储存能力、强大的学习分析能力以及更智能化的语言分析能力等,所以"机器学习"会对农业政策研究带来革命性的影响。农业经济学界要关注"机器学习"的发展,在科研和教学中导入"机器学习",结合传统的农业经济学分析方法,让农业政策的制定更加精准、更加科学、更加强大,政策沟通更加有效。
Traditional agricultural policy analysis pays more attention to the relationship between variables and estimation of model parameters,while "machine learning"focuses on the accuracy of predictions,which is precisely the purpose of agricultural policy research. Because " machine learning" has enormous data collection and storage capabilities,strong learning and analysis capabilities,and more intelligent language analysis capabilities,it could have a revolutionary impact on agricultural policy research. The agricultural economists should pay attention to the development of " machine learning",introduce " machine learning" in scientific research and teaching,and combine "machine learning"with traditional agricultural economic analysis methods to make agricultural policy formulation more precise,scientific and powerful,and make policy communication more efficient.
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