Welcome to Sklearn-Optuna's documentation

OptunaSearchCV is a drop-in replacement for Scikit-Learn's GridSearchCV and RandomizedSearchCV powered by Optuna. It extends BaseSearchCV, so fit(), score(), best_params_, cv_results_, pipelines, and clone() all work out of the box. Optuna samplers (TPE, CMA-ES, ...) explore search spaces more efficiently than grid or random search, while Optuna distributions give you log-scaled, bounded, and categorical parameter spaces.

Inspiration

This project is inspired by optuna-integration's OptunaSearchCV.

• Get Started in 5 Minutes

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  Install Sklearn-Optuna and run your first hyperparameter search.

  Getting Started

• How-to Guides

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  Task-oriented guides for samplers, callbacks, persistence, pipelines, and more.

  How-to Guides

• See It In Action

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  Explore interactive notebooks from quickstart to pipelines.

  Examples

• API Reference

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  Complete API documentation for OptunaSearchCV and wrapper classes.

  API Reference

License

This project is licensed under the terms of the Apache-2.0 License.

Acknowledgements

This project is maintained by stateful-y, an ML consultancy specializing in data science & engineering. If you're interested in collaborating or learning more about our services, please visit our website.