Identify the usage of SparkTrials as the tool that enables parallelization for tuning single-node models. Explain how SparkTrials integrates with Hyperopt to facilitate this parallelization, and discuss the advantages and limitations of using SparkTrials in this context.

Simulated

SparkTrials is only used for parallelizing model training and cannot be used for hyperparameter tuning.

2.7%

SparkTrials integrates with Hyperopt to distribute hyperparameter evaluations across a Spark cluster, enabling parallelization for tuning single-node models, but it has limitations in terms of scalability and complexity.

97.3%

SparkTrials is a standalone tool for parallelization and does not integrate with Hyperopt.

0.0%

SparkTrials is only used for tuning hyperparameters of distributed models, not single-node models.

0.0%

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Identify the usage of SparkTrials as the tool that enables parallelization for tuning single-node models. Explain how SparkTrials integrates with Hyperopt to facilitate this parallelization, and discuss the advantages and limitations of using SparkTrials in this context.