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%