摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的研究结果在一份新的报告中讨论。根据来自苏黎世的新闻，瑞士，NewsRx记者，研究表明，“在本文中，我们介绍了一个包，DDML，用于Stata中的双/去偏机器学习。”我们的新闻记者从苏黎世瑞士联邦理工学院(ETH Zurich)的研究中获得了一句话：“支持五种不同经济计量模型因果参数的估计，”允许在函数形式未知或多个外生变量的环境中灵活地估计内生变量的因果效应。DDML与Stata中许多现有的超级机器学习程序兼容。我们建议将双/去偏马赫ine学习与叠加估计相结合，将多个马赫ine学习者组合为最终预测器。根据新闻编辑的说法，研究结论是：“我们提供了蒙特卡洛证据来支持我们的建议。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news originating from Zurich, Switze rland, by NewsRx correspondents, research stated, "In this article, we introduce a package, ddml, for double/debiased machine learning in Stata." Our news journalists obtained a quote from the research from the Swiss Federal I nstitute of Technology Zurich (ETH Zurich), "Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimati on of causal effects of endogenous variables in settings with unknown functional forms or many exogenous variables. ddml is compatible with many existing superv ised machine learning programs in Stata. We recommend using double/debiased mach ine learning in combination with stacking estimation, which combines multiple ma chine learners into a final predictor." According to the news editors, the research concluded: "We provide Monte Carlo e vidence to support our recommendation."
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