If I had an imbalanced dataset with 10% positive instances and 90% negative ones, the base rate for accuracy before resampling is 90%. But what about I resampled the data such that I have an equal amount of positive and negative instances? Will 50% be my new base rate for accuracy?
I am asking this question because I found that, after resampling, my machine learning model's accuracy dropped but precision, recall, and FPR all improved on the validation set.
On a related note, will resampling techniques generally reduce the accuracy but improve precision and recall?
Thanks very much!