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Receiver operating characteristic

A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (although it can be generalized to multiple classes) at varying threshold values. ROC analysis is commonly applied in the assessment of diagnostic test performance in clinical epidemiology.

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Overview

Terminology

History

Basic concept

ROC space

Curves in ROC space

Further interpretations

Detection error tradeoff graph

Z-score

ROC curves beyond binary classification

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Receiver operating characteristic

Nodes82
Edges81
Triples168
Avg. degree1.98
Density0.02439
Components1

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Receiver operating characteristic

Top relations

related to Further reading · 145
Receiver operating characteristic → Agriculture, Analyzing Receiver Operating Characteristic, Applied Logistic Regression, Balakrishnan, Batchu, Benoit, Better Decisions, Bhagwat, Bibcode, Biomedical Informatics, Biometrics, Britaldo Soares, Calibration, Caren, Carsten, Censored Survival Data, Chad, Chemometrics, Christopher, Circulation
related to history · 11
Receiver operating characteristic → Following, For, In, It, Japanese, Pearl Harbor, ROC, ROC Accuracy Ratio, The ROC, United States, World War II
related to Radar in detail · 6
Receiver operating characteristic → As, Consider, FA, ROC, The, This

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Important terminology

roc curve positive false also auc displaystyle curves negative threshold one area rate analysis doi classifier 10 characteristic classification used

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
the Brier score.Another problem with ROC AUC is that reducing the ROC Curve to a single number ignores the fact that it is about the tradeoffs between the different systems or performance points plottedinstance ofand AUC has been linked to a number of other performance metrics0.80text
not the performance of an individual systeminstance ofand AUC has been linked to a number of other performance metrics0.80text
as well as ignoring the possibility of concavity repairinstance ofand AUC has been linked to a number of other performance metrics0.80text
so that related alternative measures such as Informednessinstance ofand AUC has been linked to a number of other performance metrics0.80text
Cohen Kappainstance ofInformedness has been shown to have desirable characteristics for Machine Learning versus other common definitions of Kappa0.80text
Fleiss Kappainstance ofInformedness has been shown to have desirable characteristics for Machine Learning versus other common definitions of Kappa0.80text
Receiver operating characteristicrelated to Further readingBalakrishnan0.60section
Receiver operating characteristicrelated to Further readingNarayanaswamy0.60section
Receiver operating characteristicrelated to Further readingHandbook0.60section
Receiver operating characteristicrelated to Further readingLogistic Distribution0.60section
Receiver operating characteristicrelated to Further readingMarcel Dekker0.60section
Receiver operating characteristicrelated to Further readingInc0.60section

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