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False positive rate (FPR): Difference between revisions
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==What is false positive rate (FPR)?== | ==What is false positive rate (FPR)?== | ||
False Positive Rate (FPR) is a performance [[metric]] used to gauge how often [[classification]] | False Positive Rate (FPR) is a performance [[metric]] used to gauge how often [[classification model]]s incorrectly classify negative instances as positives. Put differently, FPR measures the proportion of negative instances incorrectly classified as positive by the model. Calculated by dividing total false positives by total true negatives and false positives. | ||
false positive rate = [[false positive]]s / (false positives + [[true negative]]s) | false positive rate = [[false positive]]s / (false positives + [[true negative]]s) | ||
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False positive rate is like when your teacher thinks you did your homework, but you actually didn't. The false positive rate is the number of times your teacher thinks you did your homework when you didn't, divided by the total number of times your teacher thinks you did your homework. A low false positive rate means your teacher doesn't think you did your homework very often when you didn't, which is good. But sometimes it's okay for your teacher to think you did your homework when you didn't, depending on why you didn't do it. | False positive rate is like when your teacher thinks you did your homework, but you actually didn't. The false positive rate is the number of times your teacher thinks you did your homework when you didn't, divided by the total number of times your teacher thinks you did your homework. A low false positive rate means your teacher doesn't think you did your homework very often when you didn't, which is good. But sometimes it's okay for your teacher to think you did your homework when you didn't, depending on why you didn't do it. | ||
[[Category:Terms]] [[Category:Machine learning terms]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:not updated]] | ||