# Coefficients

> Coefficients - Use the Coefficients tab, which shows the positive or negative impact of important
> variables, to help you refine and optimize your models in Workbench.

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 `2026-10-09T14:05:25.051469+00:00` (UTC).

## Primary page

- [Coefficients](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/coefficients.html.md): Full documentation for this topic (Markdown sidecar).

## Sections on this page

- [Next steps](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/coefficients.html.md#next-steps): In-page section heading.

## Related documentation

- [NextGen UI documentation](https://docs.datarobot.com/en/docs/workbench/index.html.md): Linked from this page.
- [Workbench](https://docs.datarobot.com/en/docs/workbench/build-workbench/index.html.md): Linked from this page.
- [Predictive experiments](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/index.html.md): Linked from this page.
- [Evaluate models](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/index.html.md): Linked from this page.
- [Feature Impact](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/feature-impact.html.md): Linked from this page.
- [Rating Tables](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/rating-tables.html.md): Linked from this page.
- [Eureqa Models](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/eureqa.html.md): Linked from this page.

## Documentation content

| Tab | Description |
| --- | --- |
| Explanations | Displays the relative effects of the 30 most important features in the dataset (feature list). |

For [supported models](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/coefficients.html.md#supported-model-types) (linear and logistic regression), the Coefficients tab provides the relative effects of the 30 most important features, sorted (by default) in descending order of impact on the final prediction. Variables with a positive effect are displayed in red; variables with a negative effect are shown in blue. The Coefficients chart determines the following to help assess model results:

- Which features were chosen to form the prediction in the particular model?
- How important are each of these features?
- Which features have positive impact and which have negative impact?

> [!NOTE] Note
> 

The Coefficients tab is only available for a limited number of models because it is not always possible to derive the coefficients for complex models in short analytical form.

From the insight you can [export the parameters and coefficients](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/coefficients.html.md#preprocessing-and-parameter-view) that DataRobot uses to generate predictions with the selected model.

## Next steps

Compare how coefficient-based insights relate to other explanations of feature importance and model structure.

- Feature Impact : Compare the coefficient rankings against a model-agnostic view of which features most strongly drive predictions.
- Rating Tables : For GAM or GA2M models, break down how individual features contribute to predictions and export validated parameters to tune the model.
- Eureqa Models : Inspect and compare Eureqa models that balance predictive accuracy against model complexity and interpretability.