MLS-C01 · Question #389
MLS-C01 Question #389: Real Exam Question with Answer & Explanation
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Question
A data scientist uses Amazon SageMaker to perform hyperparameter tuning for a prototype machine leaming (ML) model. The data scientist's domain knowledge suggests that the hyperparameter is highly sensitive to changes. The optimal value, x, is in the 0.5 < x < 1.0 range. The data scientist's domain knowledge suggests that the optimal value is close to 1.0. The data scientist needs to find the optimal hyperparameter value with a minimum number of runs and with a high degree of consistent tuning conditions. Which hyperparameter scaling type should the data scientist use to meet these requirements?
Options
- AAuto scaling
- BLinear scaling
- CLogarithmic scaling
- DReverse logarithmic scaling
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