Social scientists are increasingly turning to supervised machine learning (SML), a set of methods optimized for using inputs from data to forecast an unobserved outcome, to offer predictions to aid policy (1). Recent work scrutinizes this approach for its suitability to social science questions (2, 3) as well as its...

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未能预测人生结局的哪些原因可以教会我们[评论]

社会科学家越来越多地转向有监督的机器学习（SML），这是一种针对使用数据输入来预测未观察到的结果进行了优化的方法，可以提供预测以帮助政策（1）。最近的工作审查了这种方法是否适合社会科学问题（2，3）以及...