Databricks Certified Machine Learning - Associate
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In the context of AutoML, explain the role of hyperparameter optimization and how AutoML can automate this process. Provide a detailed explanation of the techniques used by AutoML for hyperparameter optimization and their significance in improving model performance.
A
AutoML does not support hyperparameter optimization, as it relies on default hyperparameters for all models.
B
AutoML supports hyperparameter optimization by manually selecting a fixed set of hyperparameters for each model based on expert knowledge.
C
AutoML supports hyperparameter optimization by using techniques such as grid search, random search, and Bayesian optimization to explore the hyperparameter space and find the optimal hyperparameter values for the model.
D
AutoML supports hyperparameter optimization by automatically selecting the best hyperparameters based on the model's performance on a validation set, without exploring the hyperparameter space.