You plan to tune model hyperparameters using a sweep job in your Azure Machine Learning workspace.

You need to select a sampling method that supports both early termination for low-performance jobs and the use of continuous hyperparameters.

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

Does the proposed solution meet this goal?