Simple Rules for Complex Decisions
Simple Rules for Complex Decisions
复制标题
复杂决策的简单规则
DOI：
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复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
D. Goldstein
中科院分区：
文献类型：
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作者：
Jongbin Jung;Connor Concannon;Ravi Shroff;Sharad Goel;D. Goldstein
从诊断病人的医生到保释的法官，专家们的决定往往基于经验和直觉，而不是统计模型。虽然可以理解，但依赖直觉而不是模型往往会导致较差的结果。在这里，我们提出了一种新的方法-选择-回归-循环，用于构建对复杂决策执行良好的简单规则。这些规则采用加权清单的形式，可以在心理上应用，但仍然可以与现代机器学习算法的性能相媲美。我们创建这些规则的方法本身很简单，并且可以由具有基本统计知识的从业者执行。我们通过对司法决定在被告等待审判期间释放或拘留的详细案例研究来展示这种技术。在这个应用程序中，正如在许多政策设置中一样，拟议的决策规则的效果不能直接从历史数据中观察到：如果规则建议释放法官实际上拘留的被告，我们无法观察到在拟议的行动下会发生什么。我们通过利用因果推理的工具来解决这个关键的反事实估计问题。我们发现简单规则的表现明显优于法官，并且与基于所有可用特征训练的随机森林得出的决策相当。推广到22个不同的决策领域，我们发现这个基本结果是重复的。我们总结了一个分析框架，该框架有助于解释为什么这些简单的决策规则执行得如此之好。
From doctors diagnosing patients to judges setting bail, experts often base their decisions on experience and intuition rather than on statistical models. While understandable, relying on intuition over models has often been found to result in inferior outcomes. Here we present a new method-select-regress-and-round-for constructing simple rules that perform well for complex decisions. These rules take the form of a weighted checklist, can be applied mentally, and nonetheless rival the performance of modern machine learning algorithms. Our method for creating these rules is itself simple, and can be carried out by practitioners with basic statistics knowledge. We demonstrate this technique with a detailed case study of judicial decisions to release or detain defendants while they await trial. In this application, as in many policy settings, the effects of proposed decision rules cannot be directly observed from historical data: if a rule recommends releasing a defendant that the judge in reality detained, we do not observe what would have happened under the proposed action. We address this key counterfactual estimation problem by drawing on tools from causal inference. We find that simple rules significantly outperform judges and are on par with decisions derived from random forests trained on all available features. Generalizing to 22 varied decision-making domains, we find this basic result replicates. We conclude with an analytical framework that helps explain why these simple decision rules perform as well as they do.
DOI：
10.1257/aer.p20151023
发表时间：
2015-05
期刊：
The American economic review
影响因子：
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作者：
Kleinberg J;Ludwig J;Mullainathan S;Obermeyer Z
通讯作者：
Obermeyer Z
DOI：
10.1214/07-sts227b
发表时间：
2007-01-01
期刊：
Statistical science : a review journal of the Institute of Mathematical Statistics
影响因子：
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作者：
Tsiatis, Anastasios A;Davidian, Marie
通讯作者：
Davidian, Marie