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Beyond prediction: Using big data for policy problems
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DOI：10.1126/science.aal4321.png)
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Machine-learning prediction methods have been extremely productive in applications ranging from medicine to allocating fire and health inspectors in cities. However, there are a number of gaps between making a prediction and making a decision, and underlying assumptions need to be understood in order to optimize data-driven decision-making.
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