Table 3.

Different strategies (BEST, CROSS, RANDOM, and ADAPT) to choose a model to predict simulated test cases

Strategies	Details
BEST
A2A	Trained on A (80%), evaluated on A (20%).
B2B	Trained on B (80%), evaluated on B (20%).
CROSS
A2B	Trained on A (80%), evaluated on B (20%).
B2A	Trained on B (80%), evaluated on A (20%).
RANDOM	Randomly selected model learned from either training set of A or B to evaluate the test cases.
ADAPT	Use our proposed method to choose a model for each of the test cases.