How to calculate the precision and recall for prediction deep learning

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Dear all,
How to calculate the precision and recall for my prediction result deep learning?
my groundTruth(g.mat) is logical, and my prediction(tempSeg1.mat) also logical. All as attached.
anyone can help me?

Accepted Answer

Yatharth
Yatharth on 27 Jun 2022
Hey, can you tell more about your output matrix ? if you want to do element wise comparision of the 3d matrix then you can simply run 3 for loops like this and apply the formula.
TP=0;FP=0;TN=0;FN=0;
for i=1:128
for j=1:128
for k = 1: 64
if(idxx(i,j,k)==1 && tempSeg1(i,j,k)==1)
TP=TP+1;
elseif(idxx(i,j,k)==0 && tempSeg1(i,j,k)==1)
FP=FP+1;
elseif(idxx(i,j,k)==0 && tempSeg1(i,j,k)==0)
TN=TN+1;
else
FN=FN+1;
end
end
end
end
Precision = TP/(TP + FP)
Recall = TP /(TP + FN)

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