Show pageBacklinksCite current pageExport to PDFBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. 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), ---- 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). false_positive.txt Last modified: 2024/06/07 02:57by 127.0.0.1