MLS-C01 Practice Question: Machine Learning Implementation and Operations

Correct answer & explanation

Changing the tuning strategy from Random to Bayesian allows the tuning job to use previous results to guide the search toward more promising hyperparameter regions, which can explore the space more efficiently after plateauing. Option B is incorrect because enabling early stopping terminates underperforming trials early but does not alter the search strategy itself; it may even reduce exploration. Option C is incorrect because decreasing the maximum number of training jobs reduces the total exploration of the hyperparameter space. Option D is incorrect because increasing the number of parallel training jobs only speeds up the process but still uses the same random search strategy, which is unlikely to escape the plateau.