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Answer: Random grid
The question has conflicting requirements: iterating all possible combinations (which requires Entire Grid) while minimizing computing resources (which favors Random Grid). Based on the community discussion and Azure ML documentation, the consensus is that Random Grid (D) is the correct answer because it provides a balance - it can be configured to iterate through all possible combinations while only executing a subset, thus conserving computational resources. The documentation specifically mentions that random grid sweep yields similar results to entire grid but is more efficient computationally. Entire Grid (C) would iterate all combinations but is computationally intensive, contradicting the resource minimization requirement. Random Sweep (A) doesn't guarantee all combinations are considered, and Sweep Clustering (B) is not a valid parameter sweep mode in Azure ML Studio.
Author: LeetQuiz Editorial Team
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You are creating a binary classification model in Azure Machine Learning Studio and need to perform a hyperparameter sweep. The sweep must iterate over all possible combinations of hyperparameters while minimizing the computing resources required.
Which parameter sweep mode should you use?
A
Random sweep
B
Sweep clustering
C
Entire grid
D
Random grid
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