You plan to tune model hyperparameters using an Azure Machine Learning sweep job. You need to select a sampling method that supports both early termination for low-performance runs and the use of continuous hyperparameters.

Proposed solution: Use the random sampling method over the hyperparameter space.

Does this solution meet the goal?