科技报告详细信息
ROC Graphs: Notes and Practical Considerations for Data Mining Researchers | |
Fawcett, Tom | |
HP Development Company | |
关键词: machine learning; classification; data mining; classifier evaluation; ROC; visualization; | |
RP-ID : HPL-2003-4 | |
学科分类:计算机科学(综合) | |
美国|英语 | |
来源: HP Labs | |
【 摘 要 】
Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been increasingly adopted in the machine learning and data mining research communities. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. This article serves both as a tutorial introduction to ROC graphs and as a practical guide for using them in research. 27 Pages
【 预 览 】
Files | Size | Format | View |
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RO201804100001740LZ | 377KB | download |