An introduction to ROC analysis Export

@article{citeulike:820297, abstract = {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.}, address = {New York, NY, USA}, author = {Fawcett, Tom}, booktitle = {ROC Analysis in Pattern Recognition}, citeulike-article-id = {820297}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1159475}, citeulike-linkout-1 = {http://dx.doi.org/10.1016/j.patrec.2005.10.010}, citeulike-linkout-2 = {http://linkinghub.elsevier.com/retrieve/pii/S016786550500303X}, citeulike-linkout-3 = {http://www.sciencedirect.com/science/article/B6V15-4HV747X-1/2/c1653cca4db4e94215437a482fcbecbb}, doi = {10.1016/j.patrec.2005.10.010}, issn = {0167-8655}, journal = {Pattern Recogn. Lett.}, keywords = {classification, roc}, month = {June}, number = {8}, pages = {861--874}, posted-at = {2009-10-23 16:30:42}, priority = {2}, publisher = {Elsevier Science Inc.}, title = {An introduction to ROC analysis}, url = {http://dx.doi.org/10.1016/j.patrec.2005.10.010}, volume = {27}, year = {2006} }

TY - JOUR ID - citeulike:820297 L3 - citeulike-article-id:820297 N2 - 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. IS - 8 JF - Pattern Recogn. Lett. SN - 0167-8655 AD - New York, NY, USA EP - 874 TI - An introduction to ROC analysis PB - Elsevier Science Inc. VL - 27 T2 - ROC Analysis in Pattern Recognition SP - 861 KW - classification KW - roc AU - Fawcett, Tom PY - 2006/06// UR - http://dx.doi.org/10.1016/j.patrec.2005.10.010 ER -