论文标题
在线测试概念转移
Testing for concept shift online
论文作者
论文摘要
本说明继续研究交换性martingales，即，在任何可交换分布下的观测值下方的群落的过程。此类过程可用于检测违反IID假设的行为，这是机器学习中通常进行的。违反IID假设的行为有时被称为数据集移位，并且有时将数据集转移细分为概念转移，协变量转移等。我们的主要兴趣是概念转移，但我们还将讨论将两个组件完美分解为两个组件的交换性群众，其中一个检测概念转移，我们调用了callect chrang thect takect。我们的方法将基于共形预测技术。
This note continues study of exchangeability martingales, i.e., processes that are martingales under any exchangeable distribution for the observations. Such processes can be used for detecting violations of the IID assumption, which is commonly made in machine learning. Violations of the IID assumption are sometimes referred to as dataset shift, and dataset shift is sometimes subdivided into concept shift, covariate shift, etc. Our primary interest is in concept shift, but we will also discuss exchangeability martingales that decompose perfectly into two components one of which detects concept shift and the other detects what we call label shift. Our methods will be based on techniques of conformal prediction.
