# Eureqa advanced tuning

> Eureqa advanced tuning - Eureqa models use expressions to represent mathematical relationships and
> transformations. DataRobot provides specialized workflows for tuning Eureqa models.

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 `2026-05-01T23:10:48.113809+00:00` (UTC).

## Primary page

- [Eureqa advanced tuning](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/index.html): Full documentation for this topic (HTML).

## Related documentation

- [Reference documentation](https://docs.datarobot.com/en/docs/reference/index.html): Linked from this page.
- [Predictive AI reference](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/index.html): Linked from this page.
- [Tune Eureqa models](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/advanced-options.html): Linked from this page.
- [Configure building blocks](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/building-blocks.html): Linked from this page.
- [Building blocks reference](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/eureqa-reference.html): Linked from this page.
- [Customize target expressions](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/custom-expressions.html): Linked from this page.
- [Configure error metrics](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/error-metrics.html): Linked from this page.
- [Guidance for using error metrics](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/guidance.html): Linked from this page.
- [Configure row weighting](https://docs.datarobot.com/en/docs/reference/pred-ai-ref/eureqa-ref/row-weighting.html): Linked from this page.

## Documentation content

# Eureqa advanced tuning

Eureqa models use expressions to represent mathematical relationships and transformations. You can tune your Eureqa models by modifying building blocks, customizing the target expression, and modifying other model parameters, such as support for building blocks, error metrics, row weighting, and data splitting. To customize a Eureqa model, select the model from the Leaderboard and then click Evaluate > Advanced Tuning.

The following sections detail specialized workflows for tuning Eureqa models:

| Topic | Description |
| --- | --- |
| Tune Eureqa models | Customize Eureqa models by modifying Advanced Tuning parameters. |
| Configure building blocks | Combine and configure building blocks to create a new target expression. |
| Building blocks reference | Definitions and usage of building blocks available to Eureqa models. |
| Customize target expressions | Custom tune Eureqa models by modifying the target expression. |
| Configure error metrics | Optimize for different error metrics. |
| Guidance for using error metrics | Understand the top error metrics for different problem types. |
| Configure row weighting | Improve model performance with weighting. |