this post was submitted on 25 Nov 2023
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Machine Learning

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Hello,

I have a question that may seem trivial but which confused me because I found different approaches to doing it in different papers.

So let’s take the recall as an example : to calculate it on the test set I found two different methods in the codes available for published papers. Some calculate the recall for every image then calculate the mean on all images, other simply use the formula as if each pixel was an element in it’s own. What is the correct way to doing so ?

Thanks in advance !

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[–] jeandebleau@alien.top 1 points 10 months ago (1 children)

If all the images have the same size, it does not matter because in this case the sum of the means equals the mean of the sum.

[–] Meddhouib10@alien.top 1 points 9 months ago

How is that ? You devide by the either the pred positive pixel or the ground truth positive pixel depending of either you are calculating the recall or the precision