Databricks Certified Machine Learning - Associate
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In the context of using Hyperopt for hyperparameter tuning, what is the significance of the search space, and how does it affect the optimization process?
A
The search space is not important in the hyperparameter optimization process, as the efficiency is solely determined by the number of trials.
B
The search space defines the range of possible values for the hyperparameters and affects the exploration of the hyperparameter space during the optimization process.
C
The search space is only relevant for distributed models and does not play a role in the optimization process for single-node models.
D
The search space is a fixed component in Hyperopt and cannot be changed, so it does not affect the optimization process.