# Prediction Explanations for time-aware projects

> Prediction Explanations for time-aware projects - Compute prediction explanations for data in OTV
> and time series projects.

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 `2026-04-24T16:03:56.594330+00:00` (UTC).

## Primary page

- [Prediction Explanations for time-aware projects](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/ts-otv-predex.html): Full documentation for this topic (HTML).

## Sections on this page

- [Get Prediction Explanations](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/ts-otv-predex.html#get-prediction-explanations): In-page section heading.

## Related documentation

- [Classic UI documentation](https://docs.datarobot.com/en/docs/classic-ui/index.html): Linked from this page.
- [Modeling](https://docs.datarobot.com/en/docs/classic-ui/modeling/index.html): Linked from this page.
- [Model insights](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/index.html): Linked from this page.
- [Understand](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/index.html): Linked from this page.
- [Prediction Explanations](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/index.html): Linked from this page.
- [XEMP Prediction Explanations](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/xemp-pe.html): Linked from this page.
- [Feature Impact](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/feature-impact-classic.html): Linked from this page.

## Documentation content

# Prediction Explanations for time-aware projects

You can compute Prediction Explanations for time series and OTV projects. Specifically, you can get [XEMP Prediction Explanations](https://docs.datarobot.com/en/docs/classic-ui/modeling/analyze-models/understand/pred-explain/xemp-pe.html) for the holdout partition and sections of the training data. DataRobot only computes Prediction Explanations for the validation partition of backtest one in the training data.

## Get Prediction Explanations

The following steps provide a general overview of using the Prediction Explanations tab with time-aware projects.

1. Select a model for which you want the explanations from the Leaderboard. Then navigate to theUnderstand > Prediction Explanationstab.
2. If Feature Impact has not already been calculated for the model, click theCompute Feature Impactbutton. You can calculate impact from either thePrediction ExplanationsorFeature Impacttab as they share computational results.
3. Once the computation completes, DataRobot displays thePrediction Explanationspreview, using the default values (described below): ComponentDescription1Computation inputsSets the number of explanations to return for each record and toggles whether to apply low and/or high ranges to the selection.2Change threshold valuesSets low and high validation score thresholds for the prediction selection.3Prediction Explanations previewDisplays a preview of explanations, from the validation data, based on the input and threshold settings.4CalculatorInitiates computation of predictions and then explanations for the full selected prediction set, using the selected criteria.
4. If desired, change thecomputation inputsand/orthreshold valuesand update the preview.
5. Select the calculator icon () to begin computing Prediction Explanations for either of the datasets using the new values. DataRobot applies the default or user-specified baseline thresholds to all datasets (training, validation, test, prediction) using the same model. Whenever you modify the baseline, you must update the preview and recompute Prediction Explanations for the uploaded datasets.
6. When computation completes, download the results and view the updated display tointerpret the XEMP Prediction Explanations.