Suppose you were conducting two experiments on one dataset using a two-class boosted decision tree. In Experiment A, you set the learning parameter to 0.9 and in Experiment B, you set it to 0.03.

Which of the following scenarios is the most likely one comparatively?

Group of answer choices

Experiment A converges quickly but may miss the optimal solution.

Experiment A always converges to the best solution faster than Experiment B.

Experiment B converges faster than Experiment A to the best solution.