4 ms·
No, it means that about 50% of people scanned would trigger a "positive". The false positive rate is the number of false positives divided by the number of actu
by IanCal 7y ago
No, it means that about 50% of people scanned would trigger a "positive". The false positive rate is the number of false positives divided by the number of actual negatives.
100 people, 50 false alarms, 1 actual problem alerted and 49 marked as safe correctly = 50/(50+49) = ~50%.
- max76 7y agoThat's just wrong. This is ML 101 False positive = (Machine says positive but grand truth is negative) / (Machine says is positive) In English, a false positive is when the machine declares something as positive but it is actually negative. This fits a sanity test because ~50% of people that pass through a detector do not get patted down. The truth is closer to 10%. Even then, a true positive probably includes someone with two pennies in their pocket.
- Retric 7y agohttps://en.m.wikipedia.org/wiki/False_positive_rate https://en.m.wikipedia.org/wiki/False_positive_rate In statistics and ML it’s (FP) / (FP + TN) aka (false positives) / (actual negatives samples). This is by far the most common definition. Here ML using the common definition see fall-out: https://en.m.wikipedia.org/wiki/Precision_and_recall https://en.m.wikipedia.org/wiki/Precision_and_recall
- IanCal 7y agoYou are right this is ML 101, but you are wrong. Someone else has linked the wiki page, and I've posted it elsewhere and I would strongly recommend you read it as your interpretation is very incorrect. > In English, a false positive is when the machine declares something as positive but it is actually negative. Yes, and the rate is based on the frequency this happens in your negative set. >This fits a sanity test because ~50% of people that pass through a detector do not get patted down. The 50% figure may be wrong, but my definition of what a false positive rate is not.
- thomasahle 7y agoYou're thinking of FDR: False discovery rate. It equals Σ False positive/Σ Predicted condition positive. See https://en.m.wikipedia.org/wiki/Precision_and_recall https://en.m.wikipedia.org/wiki/Precision_and_recall for a table of different terms.
- dorgo 7y agoWow, that definition is counter-intuitive. Ive expected the false-positive-rate to be the number of false positives divided by the number of all positives. Isn't it how "rates" are usually defined? No wonder everybody is confused.
- deleted 7y ago[deleted]
- deleted 7y ago[deleted]
- IanCal 7y agoI think it's a perspective thing. You are looking at the rate of false results, so given a particular type of input what rate do you get it right? For negative ground truth your possible outputs are "false (positive)" and "true (negative)". I agree it can be confusing, but I think people would also make the opposite mistake if it were defined differently.
- thomasahle 7y agoYou're thinking of FDR: False discovery rate. It equals Σ False positive/Σ Predicted condition positive. See https://en.m.wikipedia.org/wiki/Precision_and_recall https://en.m.wikipedia.org/wiki/Precision_and_recall for a table of different terms.