Designing and Implementing a Data Science Solution on Azure — Question 143

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have an Azure Machine Learning workspace.

You plan to tune model hyperparameters by using a sweep job.

You need to find a sampling method that supports early termination of low-performance jobs and continuous hyperparameters.

Solution: Use the grid sampling method over the hyperparameter space.

Does the solution meet the goal?

Answer options

Correct answer: B

Explanation

The grid sampling method does not support early termination because it evaluates all combinations of hyperparameters exhaustively, regardless of their performance. Instead, a sampling method like Bayesian optimization would be more appropriate as it can terminate low-performing jobs early and effectively handle continuous hyperparameters.