# Period Accuracy

> Period Accuracy - Use Period Accuracy to compute error metric values for specific periods of the
> backtest validation source.

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 `2026-10-09T14:05:25.056066+00:00` (UTC).

## Primary page

- [Period Accuracy](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/period-accuracy.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/period-accuracy.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.
- [Period Accuracy](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/period-acc-classic.html.md): Linked from this page.
- [Accuracy Over Time](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/aot.html.md): Linked from this page.
- [Forecasting Accuracy](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/fcast-accuracy.html.md): Linked from this page.
- [Series Insights](https://docs.datarobot.com/en/docs/workbench/build-workbench/experiments/experiment-insights/series-insights.html.md): Linked from this page.

## Documentation content

| Tab | Description |
| --- | --- |
| Performance | Gives you the ability to specify which are the more important periods within your training dataset, which DataRobot can then provide aggregate accuracy metrics for and surface those results on the Leaderboard. |

[Period Accuracy](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/evaluate/period-acc-classic.html.md) lets you define periods within your dataset and then compare their metric scores against the metric score of the model as a whole. In other words, you can specify which are the more important periods within your training dataset, and DataRobot can then provide aggregate accuracy metrics for that period and surface those results on the Leaderboard. Periods are defined in a separate CSV file that identifies which rows to group based on the experiment’s data/time feature. Once uploaded, and with the insight calculated, DataRobot provides a table of period-based results and an “over time” histogram for each period.

## Next steps

Combine period-level results with other time-aware insights to evaluate the model's performance across the full forecast window.

- Accuracy Over Time : Visualize how predicted and actual values compare over time for the most recent backtest.
- Forecasting Accuracy : See how prediction accuracy changes at each forecast distance in the forecast window.
- Series Insights : Review distribution and metric scores across series for multiseries experiments.