That number is not especially important, as it is the 1000 legit per 1 spam ratio, they are there only to show how even very favourable numbers can result in poor performance.
I chose 0.7% because usually false positive ratio and false negative ratio are not too different. Maybe one is 5, 10 times the other, but rarely more.
The rest of your comment shows a lack of knowledge in the field of statistics: it will be hard for you to understand the issue you're stuck on without conditional probability at the very least.
Let's make it even simpler anyways.
You have 10010 works. Of those works, 10 are spam, 10000 are legitimate. You have a very good spam system thay always catches spam works (0% false negative rate) and only mistakes 1 legit work for spam ofut of 100 legit works (1% false positive rate). Your system will find all 10 real spam works, and will confuse 1% of 10000 legit works as spam. 1% of 10000 is 100. In conclusion, your system will claim to have found 110 spam works, of which only 10 are spam: that means only 1 in 11 works marked as spam will be actual spam.
The problem gets worse the more legit works there are for each spam work, and the higher the false positive rate. Clear enough?
Comment on Automatically hiding spam works
Foxglove87B Fri 24 Nov 2017 05:41PM UTC
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