A false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition (such as a disease when the disease is not present),
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In a [[ROC curve]] the [[true positive]] rate ([[Sensitivity]]) is plotted in function of the [[false positive]] rate (100-Specificity) for different cut-off points of a parameter. ... The [[area under the ROC curve]] ( [[AUC]] ) is a measure of how well a parameter can distinguish between two diagnostic groups (diseased/normal).