# Feature Effects

> Feature Effects - Feature Effects (with partial dependence) conveys how changes to the value of each
> feature change model predictions.

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 `2026-04-24T16:03:56.751701+00:00` (UTC).

## Primary page

- [Feature Effects](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/experiment-insights/feature-effects.html): Full documentation for this topic (HTML).

## Related documentation

- [NextGen UI documentation](https://docs.datarobot.com/en/docs/workbench/index.html): Linked from this page.
- [Workbench](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/index.html): Linked from this page.
- [Predictive experiments](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/index.html): Linked from this page.
- [Evaluate models](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/experiment-insights/index.html): Linked from this page.
- [Feature Effects](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/feature-effects-classic.html): Linked from this page.

## Documentation content

# Feature Effects

| Tab | Description |
| --- | --- |
| Explanation | Shows the effect of changes in the value of each feature on model predictions. |

[Feature Effects](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/feature-effects-classic.html) answers the question—how does a model "understand" the relationship between each feature and the target? It is an on-demand feature, dependent on the [Feature Impact](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/experiment-insights/feature-effects.html#feature-impact) calculation, which is prompted for when first opening the visualization. The insight is communicated in terms of [partial dependence](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/feature-effects-classic.html#partial-dependence-logic), an illustration of how changing a feature's value, while keeping all other features as they were, impacts a model's predictions.