# LIME explanations for models

> LIME explanations for models - Apply Local Interpretable Model-agnostic Explanations (LIME) to
> models built and deployed with DataRobot.

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 `2026-05-06T18:17:09.583921+00:00` (UTC).

## Primary page

- [LIME explanations for models](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/run-lime.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.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Model evaluation and metrics](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/model-eval-metrics/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/main/advanced_ml_and_api_approaches/LIME%20with%20DataRobot%20Models/LIME%20analysis%20with%20DataRobot.ipynb)

This accelerator shows how you can apply Local Interpretable Model-agnostic Explanations (LIME) to models built and deployed with DataRobot. LIME serves as another method in your toolbox to explain model predictions, complementing the built-in DataRobot capabilities of XEMP and SHAP prediction explanations.

The accelerator demonstrates how to:

- Connect to DataRobot using the API.
- Build and deploy a model in DataRobot.
- Execute LIME analysis with the deployed model.