A binary classifier achieves 95% accuracy on a test set consisting of 95% positive and 5% negative instances. If we use the same classifier on a test set composed of 50% positive and 50% negative instances, we expect to get:

A. lower accuracy

B. the same accuracy

C. higher accuracy

D. cannot be determined