In the context of using Hyperopt for hyperparameter tuning, explain the concept of a 'trial' and its role in the optimization process. How does the outcome of a trial influence the subsequent trials in the search for optimal hyperparameters?

Simulated

A trial is a single evaluation of the objective function with a specific set of hyperparameters, and its outcome has no influence on the subsequent trials.

42.4%

A trial is a group of evaluations of the objective function with different hyperparameters, and its outcome is used to guide the search in subsequent trials.

39.4%

A trial is a process of randomly selecting hyperparameters and evaluating the objective function, and its outcome is not considered in the optimization process.

15.2%

A trial is a fixed set of hyperparameters that are used throughout the optimization process, and its outcome is not considered in the search for optimal hyperparameters.

3.0%

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In the context of using Hyperopt for hyperparameter tuning, explain the concept of a 'trial' and its role in the optimization process. How does the outcome of a trial influence the subsequent trials in the search for optimal hyperparameters?