Consider a scenario where you are tuning hyperparameters for a Spark ML model using Hyperopt. Describe how you would set up the Trials object to parallelize the tuning process and what considerations you need to make regarding the number of trials versus the model's accuracy.

Simulated

The Trials object should be configured to run sequentially without parallelization to ensure stability.

10.0%

Parallelizing with Trials can be done by setting up a Spark cluster and distributing the trials across nodes, but this may not necessarily improve accuracy.

80.0%

Increasing the number of trials always leads to higher accuracy, so more trials should always be preferred.

0.0%

Parallelization is not possible with Hyperopt when using Spark ML models.

10.0%

Databricks Certified Machine Learning - Associate

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Consider a scenario where you are tuning hyperparameters for a Spark ML model using Hyperopt. Describe how you would set up the Trials object to parallelize the tuning process and what considerations you need to make regarding the number of trials versus the model's accuracy.