Compare model types with Hyperopt and MLflow
Note
The open-source version of Hyperopt is no longer being maintained.
Hyperopt is no longer pre-installed on Databricks Runtime ML 17.0 and above. Azure Databricks recommends using Optuna instead 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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