# Feature selection notebooks

> Feature selection notebooks - Review notebooks that outline feature selection.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-01T23:10:47.762175+00:00` (UTC).

## Primary page

- [Feature selection notebooks](https://docs.datarobot.com/en/docs/api/dev-learning/python/py-code-examples/modeling-code/feat-select/index.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [Python API client user guide](https://docs.datarobot.com/en/docs/api/dev-learning/python/index.html): Linked from this page.
- [Python code examples](https://docs.datarobot.com/en/docs/api/dev-learning/python/py-code-examples/index.html): Linked from this page.
- [Modeling code examples](https://docs.datarobot.com/en/docs/api/dev-learning/python/py-code-examples/modeling-code/index.html): Linked from this page.
- [Feature Importance Rank Ensembling](https://docs.datarobot.com/en/docs/api/dev-learning/python/py-code-examples/modeling-code/feat-select/Feature-Importance-Rank-Ensembling.html): Linked from this page.
- [Advanced feature selection with Python](https://docs.datarobot.com/en/docs/api/dev-learning/python/py-code-examples/modeling-code/feat-select/python-select.html): Linked from this page.

## Documentation content

# Feature selection notebooks

DataRobot offers end-to-end code examples via Jupyter notebooks that help you find complete examples of common data science and machine learning workflows.
Review the notebooks that outline feature selection below.

| Topic | Describes... |
| --- | --- |
| Feature Importance Rank Ensembling | Learn about the benefits of Feature Importance Rank Ensembling (FIRE)—a method of advanced feature selection that uses a median rank aggregation of feature impacts across several models created during a run of Autopilot. |
| Advanced feature selection with Python | Use Python to select features by creating aggregated Feature Impact. |