Designing and Implementing a Data Science Solution on Azure — Question 9

You create a binary classification model by using Azure Machine Learning Studio.
You must tune hyperparameters by performing a parameter sweep of the model. The parameter sweep must meet the following requirements:
✑ iterate all possible combinations of hyperparameters
✑ minimize computing resources required to perform the sweep
You need to perform a parameter sweep of the model.
Which parameter sweep mode should you use?

Answer options

Correct answer: C

Explanation

The correct answer is 'Entire grid' because it systematically explores every combination of hyperparameters, ensuring thorough coverage for optimization. The other options like 'Random sweep' and 'Random grid' do not guarantee all combinations are tested, while 'Sweep clustering' is not a recognized method for hyperparameter tuning.