Databricks Certified Machine Learning - Associate
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Given a Spark ML model and a dataset, how would you use Hyperopt to perform Bayesian hyperparameter inference for distributed models? Provide a code snippet that demonstrates the integration of Hyperopt with Spark MLlib for this purpose.
Given a Spark ML model and a dataset, how would you use Hyperopt to perform Bayesian hyperparameter inference for distributed models? Provide a code snippet that demonstrates the integration of Hyperopt with Spark MLlib for this purpose.
Simulated
Explanation:
To perform Bayesian hyperparameter inference for distributed models using Hyperopt, you can create a custom Spark ML estimator that wraps the Spark ML model and its hyperparameters. Then, you can use Hyperopt's fmin function to define the search space and optimize the hyperparameters of the custom estimator. This integration allows you to leverage Hyperopt's capabilities for Bayesian hyperparameter inference while working with distributed models in Spark MLlib.