接收机工作特性
计算机科学
机器学习
人工智能
简单(哲学)
数据挖掘
模式识别(心理学)
哲学
认识论
标识
DOI:10.1016/j.patrec.2005.10.010
摘要
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.
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