ROC Graphs: Notes and Practical Considerations for Researchers Export

@misc{citeulike:622672, abstract = {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 ...}, author = {Fawcett, T.}, citeulike-article-id = {622672}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.9777}, posted-at = {2006-05-11 07:32:58}, priority = {2}, title = {ROC Graphs: Notes and Practical Considerations for Researchers}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.9777}, year = {2004} }

TY - GEN ID - citeulike:622672 L3 - citeulike-article-id:622672 N2 - 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 ... TI - ROC Graphs: Notes and Practical Considerations for Researchers AU - Fawcett, T PY - 2004/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.9777 ER -