<sod>Sensitivity therefore quantifies the avoiding of [[false positives and false negatives|false negatives]], and specificity does the same for [[false positives and false negatives|false positives]].  For any test, there is usually a trade-off between the measures - for instance, in [[airport security]] since testing of passengers is for potential threats to safety, scanners may be set to trigger alarms on low-risk items like belt buckles and keys (low specificity), in order to increase the probability of identifying dangerous objects and minimize the risk of missing objects that do pose a threat (high sensitivity). This trade-off can be represented graphically using a [[receiver operating characteristic]] curve.  A perfect predictor would be described as 100% sensitive (e.g., all sick individuals are correctly identified as sick) and 100% specific (e.g., no healthy individuals are incorrectly identified as sick); in reality any non-deterministic predictor will possess a minimum [[error bound]] known as the [[Bayes error rate]].<eod>
<sod>Sensitivity therefore quantifies the avoiding of [[false positives and false negatives|false negatives]], and specificity does the same for [[false positives and false negatives|false positives]].  For any test, there is usually a trade-off between the measures - for instance, in [[airport security]] since testing of passengers is for potential threats to safety, scanners may be set to trigger alarms on low-risk items like belt buckles and keys (low specificity), in order to increase the probability of identifying dangerous objects and minimize the risk of missing objects that do pose a threat (high sensitivity). This trade-off can be represented graphically using a [[receiver operating characteristic]] curve.  A perfect predictor would be described as 100% sensitive (e.g., all sick individuals are correctly identified as sick) and 100% specific (e.g., no healthy individuals are incorrectly identified as sick); in reality any [[non-deterministic_algorithm|non-deterministic]] predictor will possess a minimum [[error bound]] known as the [[Bayes error rate]].<eod>