DATABRICKS-MLP Question 27

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• Chose A0

  - Correct answer : A — Hyperopt is removed from Databricks Runtime ML after version 16.4 LTS, and current Databricks guidance recommends Optuna, with MLflow 3 integration, or Ray Tune instead. A . Databricks removed Hyperopt from Databricks Runtime ML after the 16.4 LTS release, and current documentation points teams toward Optuna, which integrates with MLflow 3 through `MlflowStorage` and `MlflowSparkStudy`, or toward Ray Tune for distributed search. B . This is the opposite of current guidance: Hyperopt is deprecated on current runtimes, and teams starting new projects are directed toward Optuna or Ray Tune rather than continuing to rely on `SparkTrials`. C . `MlflowSparkStudy` is part of the newer Optuna-with-MLflow-3 integration, not a renamed version of Hyperopt's `SparkTrials`; the two come from different libraries with different APIs. D . Hyperopt's removal from Databricks Runtime ML after 16.4 LTS applies regardless of whether it is tuning a Spark ML estimator or a single-node scikit-learn model, so it is not selectively deprecated by model type.