Compare model types with Hyperopt and MLflow

Note

The open-source version of Hyperopt is no longer being maintained.

Hyperopt will be removed in the next major DBR ML version. Databricks recommends using Optuna for a similar experience and access to more up-to-date hyperparameter tuning algorithms.

This notebook demonstrates how to tune the hyperparameters for multiple models and arrive at a best model overall. It uses Hyperopt with SparkTrials to compare three model types, evaluating model performance with a different set of hyperparameters appropriate for each model type.

Compare models using scikit-learn, Hyperopt, and MLflow notebook

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