# Manage experiments

> Manage experiments - Provides access to the data insights and the model Leaderboard where you can
> evaluate forecasting e models.

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 `2026-05-06T18:17:10.069850+00:00` (UTC).

## Primary page

- [Manage experiments](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/index.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.
- [add or retrain models](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-add.html): Linked from this page.
- [create custom blueprints](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-cml.html): Linked from this page.
- [Experiment setup](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/exp-setup.html): Linked from this page.
- [Data preview](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-data.html#data-preview-tile): Linked from this page.
- [Blueprint repository](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/blueprint-repo.html): Linked from this page.
- [Model Leaderboard](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/leaderboard.html): Linked from this page.
- [insights](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/experiment-insights/index.html): Linked from this page.
- [Experiment insights](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-insights-tile.html): Linked from this page.
- [Model comparison](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/compare-models.html): Linked from this page.

## Documentation content

After modeling has started, DataRobot constructs a model Leaderboard to help learn and understand models and the data that built them. Also from the Leaderboard you can [add or retrain models](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-add.html) and [create custom blueprints](https://docs.datarobot.com/en/docs/workbench/nxt-workbench/experiments/manage-experiments/experiment-cml.html) from the Leaderboard blueprint using built-in tasks and custom Python/R code.

Tiles on the left-side of the experiment Leaderboard provide all the tools necessary for managing predictive experiments. They are described in the following section:

| Tile | Name | Description |
| --- | --- | --- |
|  | Experiment setup | Opens the experiment setup summary page. |
|  | Data preview | Displays a more visual representation of the features in your dataset, including frequent values. |
|  | Features | Displays features in a table format alongside feature importance and summary statistics. Select specific features to view more detailed data insights than those shown on the Data preview tile. |
|  | Feature lists | Allows you to create new feature lists, manage existing ones, and retrain all the models in an experiment on a different feature list. |
|  | Data insights | Helps you track and visualize associations within your data using the Feature Associations insight. |
|  | Blueprint repository | Opens library of modeling blueprints available for a selected experiment. |
|  | Model Leaderboard | Opens a list of all built models and overview information for each. Provides access to the model's available insights. |
|  | Experiment insights | Opens experiment-level insights for all models. |
|  | Model comparison | Opens a tool for comparing compatible models within or across experiments. Model comparison is not available for time-aware experiments but for Use Cases with non-time-aware experiments, you can initiate a compare from within a time-aware experiment. |