论文标题
交换性，保形预测和等级测试
Exchangeability, Conformal Prediction, and Rank Tests
论文作者
论文摘要
近年来，在机器学习和统计数据中，保形预测一直是一种非常流行的无分配预测推断方法。它的受欢迎程度源于以下事实：它围绕着任何预测算法（例如神经网络或随机森林）的包装器。交换性是共形预测有效性的核心。交换性的概念也是在非参数统计中广为人知的等级测试的核心。在本文中，我们回顾了交换性的概念，并讨论了对共形预测和等级测试的影响。我们为这些主题提供低级介绍，并讨论保形预测与等级测试之间的相似之处。
Conformal prediction has been a very popular method of distribution-free predictive inference in recent years in machine learning and statistics. Its popularity stems from the fact that it works as a wrapper around any prediction algorithm such as neural networks or random forests. Exchangeability is at the core of the validity of conformal prediction. The concept of exchangeability is also at the core of rank tests widely known in nonparametric statistics. In this paper, we review the concept of exchangeability and discuss the implications for conformal prediction and rank tests. We provide a low-level introduction to these topics, and discuss the similarities between conformal prediction and rank tests.
