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- Receiver_operating_characteristic abstract "In signal detection theory, a receiver operating characteristic (ROC), or simply ROC curve, is a graphical plot which illustrates the performance of a binary classifier system as its discrimination threshold is varied. It is created by plotting the fraction of true positives out of the total actual positives (TPR = true positive rate) vs. the fraction of false positives out of the total actual negatives (FPR = false positive rate), at various threshold settings. TPR is also known as sensitivity or recall in machine learning. The FPR is also known as the fall-out and can be calculated as one minus the more well known specificity. The ROC curve is then the sensitivity as a function of fall-out. In general, if both of the probability distributions for detection and false alarm are known, the ROC curve can be generated by plotting the Cumulative Distribution Function (area under the probability distribution from -inf to +inf) of the detection probability in the y-axis versus the Cumulative Distribution Function of the false alarm probability in x-axis.ROC analysis provides tools to select possibly optimal models and to discard suboptimal ones independently from (and prior to specifying) the cost context or the class distribution. ROC analysis is related in a direct and natural way to cost/benefit analysis of diagnostic decision making.The ROC curve was first developed by electrical engineers and radar engineers during World War II for detecting enemy objects in battlefields and was soon introduced to psychology to account for perceptual detection of stimuli. ROC analysis since then has been used in medicine, radiology, biometrics, and other areas for many decades and is increasingly used in machine learning and data mining research.The ROC is also known as a relative operating characteristic curve, because it is a comparison of two operating characteristics (TPR and FPR) as the criterion changes.".
- Receiver_operating_characteristic thumbnail Roccurves.png?width=300.
- Receiver_operating_characteristic wikiPageExternalLink 654.full.
- Receiver_operating_characteristic wikiPageExternalLink download?doi=10.1.1.97.9674&rep=rep1&type=pdf&ei=GpRGT_juOo3H0AH3quCqDg&usg=AFQjCNHvAiRwGwk8mRE7sMtPEOKXClmCsA&cad=rja.
- Receiver_operating_characteristic wikiPageExternalLink j.chemolab.2005.05.004.
- Receiver_operating_characteristic wikiPageExternalLink index.html.
- Receiver_operating_characteristic wikiPageExternalLink ROC101.pdf.
- Receiver_operating_characteristic wikiPageExternalLink roc.
- Receiver_operating_characteristic wikiPageExternalLink 433.abstract.
- Receiver_operating_characteristic wikiPageExternalLink index.html.
- Receiver_operating_characteristic wikiPageExternalLink roc.
- Receiver_operating_characteristic wikiPageExternalLink javarad.
- Receiver_operating_characteristic wikiPageExternalLink roc.
- Receiver_operating_characteristic wikiPageExternalLink roc.html.
- Receiver_operating_characteristic wikiPageID "922505".
- Receiver_operating_characteristic wikiPageRevisionID "604828750".
- Receiver_operating_characteristic hasPhotoCollection Receiver_operating_characteristic.
- Receiver_operating_characteristic subject Category:Biostatistics.
- Receiver_operating_characteristic subject Category:Data_mining.
- Receiver_operating_characteristic subject Category:Detection_theory.
- Receiver_operating_characteristic subject Category:Socioeconomics.
- Receiver_operating_characteristic subject Category:Statistical_classification.
- Receiver_operating_characteristic subject Category:Summary_statistics_for_contingency_tables.
- Receiver_operating_characteristic comment "In signal detection theory, a receiver operating characteristic (ROC), or simply ROC curve, is a graphical plot which illustrates the performance of a binary classifier system as its discrimination threshold is varied. It is created by plotting the fraction of true positives out of the total actual positives (TPR = true positive rate) vs. the fraction of false positives out of the total actual negatives (FPR = false positive rate), at various threshold settings.".
- Receiver_operating_characteristic label "Característica de Operação do Receptor".
- Receiver_operating_characteristic label "Curva ROC".
- Receiver_operating_characteristic label "ROC-curve".
- Receiver_operating_characteristic label "ROC-кривая".
- Receiver_operating_characteristic label "ROC曲线".
- Receiver_operating_characteristic label "Receiver Operating Characteristic".
- Receiver_operating_characteristic label "Receiver Operating Characteristic".
- Receiver_operating_characteristic label "Receiver operating characteristic".
- Receiver_operating_characteristic label "Receiver operating characteristic".
- Receiver_operating_characteristic label "受信者操作特性".
- Receiver_operating_characteristic sameAs Receiver_Operating_Characteristic.
- Receiver_operating_characteristic sameAs Curva_ROC.
- Receiver_operating_characteristic sameAs Receiver_Operating_Characteristic.
- Receiver_operating_characteristic sameAs Receiver_operating_characteristic.
- Receiver_operating_characteristic sameAs 受信者操作特性.
- Receiver_operating_characteristic sameAs 수신자_조작_특성.
- Receiver_operating_characteristic sameAs ROC-curve.
- Receiver_operating_characteristic sameAs Característica_de_Operação_do_Receptor.
- Receiver_operating_characteristic sameAs m.0280vqc.
- Receiver_operating_characteristic sameAs Q327120.
- Receiver_operating_characteristic sameAs Q327120.
- Receiver_operating_characteristic wasDerivedFrom Receiver_operating_characteristic?oldid=604828750.
- Receiver_operating_characteristic depiction Roccurves.png.
- Receiver_operating_characteristic isPrimaryTopicOf Receiver_operating_characteristic.
