An introduction to ROC analysis
An introduction to ROC analysis
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DOI：
10.1016/j.patrec.2005.10.010
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发表时间：
2006-06-01
影响因子：
5.1
通讯作者：
Fawcett, Tom
中科院分区：
文献类型：
--
作者：
Fawcett, Tom
接收器操作特征 (ROC) 图对于组织分类器和可视化其性能非常有用。 ROC图常用于医疗决策，近年来在机器学习和数据挖掘研究中的使用越来越多。尽管 ROC 图看起来很简单，但在实践中使用它们时存在一些常见的误解和陷阱。本文的目的是介绍 ROC 图并作为在研究中使用它们的指南。 (c) 2005 Elsevier B.V. 保留所有权利。
Receiver operating characteristics (ROC) graphs are useful for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been used increasingly in machine learning and data mining research. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research. (c) 2005 Elsevier B.V. All rights reserved.