# ROC Curve

> ROC Curve - The ROC Curve tools help you explore classification, performance, and statistics related
> to a selected model at any point on the probability scale.

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 `2026-10-09T14:05:25.056917+00:00` (UTC).

## Primary page

- [ROC Curve](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/roc-curve.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/roc-curve.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.
- [ROC Curve](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/roc-curve-tab/roc-curve-classic.html.md): Linked from this page.
- [Cumulative charts](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/roc-curve-tab/cumulative-charts-classic.html.md): Linked from this page.
- [confusion matrix](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/roc-curve-tab/confusion-matrix-classic.html.md): Linked from this page.
- [payoff matrix/profit curve](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/roc-curve-tab/profit-curve-classic.html.md): Linked from this page.
- [Metrics](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/roc-curve-tab/metrics-classic.html.md): Linked from this page.
- [Confusion Matrix](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/confusion-matrix.html.md): Linked from this page.
- [Lift Chart](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/lift-chart.html.md): Linked from this page.
- [Metric Scores](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/metric-scores.html.md): Linked from this page.

## Documentation content

| Tab | Description |
| --- | --- |
| Performance | Helps in exploring classification, performance, and statistics related to a selected model at any point on the probability scale. |

For classification experiments, the ROC Curve tab provides the following tools:

- An ROC Curve
- Cumulative charts
- A confusion matrix
- A payoff matrix/profit curve
- Metrics

## Next steps

Continue evaluating your classification model with these related insights.

- Confusion Matrix : Evaluate model performance for multiclass experiments using a confusion matrix.
- Lift Chart : See how well the model segments the target population and ranks predictions from low to high.
- Metric Scores : Review the model's performance across all supported metrics.