In my CNN, I have 200 'negative' images and 50 'positive' images in my test set and I want to make a confusion matrix. My doubt is if I have to equalize the samples in the dataset because if I keep this 200 - 50 my precision falls because I have a lot of 'false positives'.

So, I have to divide the percentage of negatives by 50, or keep 200/50?

This is my results without balance the samples:

                    predicted positive         predicted negative
actual pos.              41                             9
actual neg.              31                            169

recall = 41 / 50 = 82%
precision = 41 / 72 = 57%