5 ms·
That'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 positi
by max76 7y ago
That'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.