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Edit applications

On the Applications tab, click Open next to the application you want to manage and click Build. The Build page allows you to modify the configuration of an application using widgets. Before the app opens, you must sign in with DataRobot and authorize access. To test a new configuration end-user application, click Go to app.

  Element Description
Pages panel Allows you to rename, reorder, add, hide, and delete application pages.
Widget panel Allows you to add widgets to your application.
Settings Modifies general configurations and permissions as well as displays app usage.
Documentation Opens the DataRobot documentation for No-Code AI Apps.
Editing page dropdown Controls the application page you are currently editing. To view a different page, click the dropdown and select the page you want to edit. Click Manage pages to open the Pages panel.
Preview Previews the application on different devices.
Go to app / Publish Opens the end-user application, where you can make new predictions, as well as view prediction results and widget visualizations. After editing an application, this button displays Publish, which you must click to apply your changes.
Widget actions Moves, hides, edits, and deletes widgets.


Pages divide an application into separate sections that you can navigate between—allowing you to organize and group insights in a way that makes sense for your use case. By default, each application has the following pages:

Page Description
Home The application landing page.
Create Prediction The single record prediction page.
Prediction Details The prediction results page.

Default pages cannot be deleted; however, the Create Prediction page can be renamed.

To manage your pages, click the Pages panel icon on the left or open the Editing page dropdown and click Manage pages.

In the Pages panel, you can:

  Element Description
+ Add Adds a new page to the application.
Reorder Modifies the order of the pages.
Rename Renames a page.
More options Deletes or hides a page. Default pages (listed above) cannot be deleted.
Editing page Controls the application page you are currently editing.

Pages are displayed at the top of the application.


Applications are composed of widgets that create visual, interactive, and purpose-driven end-user applications. There are two types of widgets available—chart widgets and header widgets. All widgets must be configured before using an application. If a widget is not configured or is configured incorrectly, DataRobot displays an error message.

To add a widget to your application, click the Widget panel in the upper-left corner, then drag-and-drop a widget from the left pane into the canvas.

Default widgets

Applications automatically include several default widgets to make predictions and view prediction results. While these widgets are preconfigured by DataRobot, you can further customize them in Build mode. The table below lists each default widget and the available customization options:

Widget Page Description Customization options
Add Data Home Allows you to upload prediction files.
  • Rename widget
All Rows Home Displays prediction history by row.
  • Rename widget
  • Add/remove features
  • Include adjusted threshold prediction column for binary projects
  • Add action to download rows
  • Add action to delete rows
Add New Row Create Prediction Allows you to make single record predictions.
  • Rename widget, add row button, and cancel button
  • Add/remove feature fields
  • Enable option for populating averages toggle.
General Information Prediction Details Displays feature values you want to view for each prediction that don't necessarily impact the results.
  • Rename widget
  • Add/remove feature fields
Prediction Information Prediction Details Displays feature values likely to impact the prediction, as well as Prediction Explanations.
  • Rename widget
  • Add/remove feature fields
Prediction Explanations Prediction Details Displays a chart with prediction results and a table with Prediction Explanations.
  • Rename widget
  • Add description
  • Color settings

Header widgets

Header widgets provide additional filtering options within an application. Parameters specified in a filtering widget are applied to all visible chart widgets.

Header widget descriptions

The table below describes the available header widgets:

Widget Description
Categories Filters by one or more categorical features.
Dates Filters by date features.
Numbers Filters by numeric features. You must define a Min and Max in the widget properties.

To configure a header widget, click the widget and select a feature to filter on. If there are no results in the filter drop-down, the dataset doesn’t include the required feature type.

Chart widgets

Chart widgets add visualizations to an application and can be configured to surface important insights in your data and prediction results. For many of the chart widgets, you must select both:

  • Dimensions: Features that contain qualitative values used to categorize and reveal details in data.
  • Measures: Features with numeric, quantitative values that can be measured.

Chart widget descriptions

The table below describes the available chart widgets:

Widget Description
Line Displays a Line chart for the selected features—useful for visualizing trends, understanding the distribution of your data, comparing values in larger datasets, and understanding the relationship between value sets.
Bar Displays a Bar chart for the selected features—useful for understanding the distribution of your data and comparing values in smaller datasets.
Line + Bar Displays a Line and Bar chart for the selected features. You can toggle between the two in the open application.
Area Displays an Area chart for the selected features—useful for visualizing the composition of data.
Donut Displays a pie chart based on one dimension and one measure—useful for visualizing the composition of data, especially how individual parts compare to the whole.
Single Value Displays the average value of the selected feature.

To configure a chart widget:

  1. Click to select the widget. The active selection is displayed in the left pane.
  2. Click Manage. The Manage Feature window appears.

  3. In the Dimensions tab, click the orange arrows next to one or more features you’d like to visualize on the x-axis. You can select categorical, date, and boolean features.

    Viewing feature details

    In the Manage Feature window, click a feature to view a histogram of the feature values in the training data.

    Instead of a histogram, location feature types display a static map with the training data represented by data points.

  4. Click Measures and click the arrow next to the feature you'd like to measure on the y-axis. The Measures tab only displays numeric and custom features.

  5. Click Save to apply the configuration.

  6. With a widget selected, use the Data and Properties tabs to further customize its appearance and behavior.


You must select at least one dimension and one measure to configure a widget (with the exception of the Single Value widget).

If the widget displays a yellow error message stating there is no valid data, the application does not have access to the training data. You must create a project from the dataset in the AI Catalog.

Custom features

Similar to feature transformations in the main DataRobot platform, you can create custom features for chart widgets in your application.

  1. In the Manage Feature window, click Add custom feature.

  2. Name the custom feature, then type the function and features using the supported syntax. The example below measures the cost of shipments per kilogram.

  3. Click Create. The custom feature appears in the Measures tab of the Manage Features window.


You can only use numeric features to create custom feature expressions.

What-if and Optimizer

The What-if and Optimizer widget provides two tools for interacting with prediction results:

  • What-if: A decision-support tool that allows you to create and compare multiple prediction simulations to identify the option that provides the best outcome. You can also make a prediction, then change one or more inputs to create a new simulation, and see how those changes affect the target feature.
  • Optimizer: Identifies the maximum or minimum predicted value for a target by varying the values of a selection of flexible features in the model.

The What-if and Optimizer widget can be a scenario comparison tool, a scenario optimizer tool, or both.

To access the What-if and Optimizer widget, open the Editing page dropdown and select Prediction Details.

With the widget selected, click Properties.

The app offers a number of settings that enhance the output of predicted values for your target. The table below describes each configurable parameter:

Parameter Description
What-if and Optimizer toggles Enable scenario what-if: Toggle to enable or disable the comparison functionality.

Enable scenario optimizer: Toggle to enable or disable the optimizer functionality. If optimizer is enabled, you must select an option under Outcome of optimal scenario and can include a custom optimization expression.
Outcome of optimal scenario Sets whether to minimize or maximize the predicted values for the target feature. Minimizing leads to the lowest outcome (e.g., custom churn), and maximizing the highest (e.g., sale price).
Custom optimization expression Allows inclusion of more than one target feature in your optimization. Create an equation contained in curled braces that uses one or more features, such as {converted} * {renewal_price}.
Set optimization algorithm If enabled, choose from the algorithms listed and determine the number of simulations to run. Choose from the Grid Search, Particle Swarm, and Hyperopt algorithms or allow DataRobot to select the best algorithm for your selection of features.

Grid Search is an exhaustive, brute-force search of options on up to three flexible features. This may have long run time because it tries many possibilities, even if prior iterations don't suggest a strong outcome.

Particle Swarm is a metaheuristic strategy that tests a large number of options with up to 30 flexible features. It can be effective for numeric flexible features but may not be as effective for flexible categorical features.

Hyperopt efficiently explores significantly fewer options on up to 20 flexible features. It is effective for categorical and numeric features. With this algorithm, you can set up to 400 simulations. More iterations may yield better results, but can result in longer run times as it takes many iterations to converge.
Constrain sum of features Constraints ensure that each record’s optimization iterations don’t output results that exceed a given value for the target feature. For example, if you are optimizing the price of a home, you may want to expand the gross living area by finishing part of the basement or adding a bedroom. You can use a sum constraint to limit the space each project is allowed to occupy in sq/ft. Choose Maximum (selected solutions must never exceed) or Equality (selected solutions must be equal) to the constrain value.
Views Display the information as a chart, a table, or both.


The default configuration is determined by the template selected during app creation. The What-if and Optimizer widget is disabled for the Predictor template but can be enabled by clicking the Eye icon.

Custom optimization expressions

For batch prediction optimization, use a field defined in the batch upload as part of the custom optimization expression the same way you use a feature from the dataset that the app is deployed from. For example, if you label a field in a spreadsheet net_profit, and you have a time_to_market feature in the project's underlying dataset, the following would be a valid custom expression:

Add constraints to custom expressions

Not only can you use custom expressions to specify an optimal outcome by modifying the distance to a target number (instead of just minimizing or maximizing the predicted value for the target), you can also use custom expressions to add constraints on conditions of other flexible features. To do this, you must add a constraint to the custom expression as a penalty term.

For example, your target feature is sales and you want to maximize sales while monitoring how much is being spent on marketing (e.g., youtube and tv ads). To do this, you want to make sure overspending on marketing is penalized appropriately—overspending by $1.00 should be less penalized than overspending by $1,000,000.

If you have a marketing budget of $100,000 to split between youtube and tv ads, the custom expression might look like this:

    - (((youtube_spend + tv_spend) > 100000) * factor1)
    - ((youtube_spend + tv_spend) * factor2)

factor1 represents how much you want to penalize for overspending, and factor2 represents how much you want to penalize for spending in general.

factor2 can be thought of as the marketing ROI. If your industry expects a 3% ROI for marketing then this value would be 1.03

Constrain sum of features

To select the features that you want to be part of the sum:

  1. Turn on Constrain sum of features at the bottom of the Properties tab. Under Part of sum features, click Select.

  2. In the Manage Features window, check the box next to at least two fixed or flexible features—the selected features must be numeric. This option is not available if you use the Hyperopt algorithm.

  3. Click Save when you are finished selecting features.

Flexible features

The Data tab allows you to select the features that represent the factors you have control over when searching for your optimized outcome. For example, when optimizing the price of homes, some flexible features are the quality of the kitchen, the cost of the mortgage, and the size of the garage.

To manage flexible features:

  1. Click Manage.

  2. Use the orange arrows to add or remove features.

  3. Click Save to confirm your flexible features.


When you have selected flexible features, you can apply constraints to them. This instructs the app to only include values falling in the range determined by numeric constraints or specific values for a categorical feature.

To apply constraints to a feature, click Set Constraints on the Data tab.

Selecting a flexible feature expands a dropdown displaying the feature distribution.

For categorical features, open the Search from categories dropdown and choose which features to include in the simulation by checking the corresponding box.

For numeric features, you can enter individual values for the minimum and maximum numeric ranges or drag the boundaries on the histogram.

Toggle Integer values on to include only integer values (exclude decimals).

Click Save to confirm your feature constraints.


When editing an application, click the Settings tab.

The General Configuration tab allows you to edit the following settings:

Setting Description
App name Set the application name.
App description Add a description for the application.
Prediction decimal places Set the number of decimal places displayed for predictions. Affects the All Rows widget, Prediction Explanations, and What-if and Optimizer widget.
CSV export Toggle on Include BOM to include the byte order mark in exports.

Click Save to apply any changes made to the general configuration settings.

The Permissions tab allows you to manage access to the application and share it with other users, groups, and organizations, including those without access to DataRobot. The options on this page vary depending on which option you've selected in the Who can access the app dropdown.

  • If you select Invited user only, you can only share the application with users, groups, and organizations.

  • If you select Anyone with the Sharing Link, you can share the application with users, groups, organizations, as well as users outside of DataRobot with the shareable link generated in the field below Link sharing on (1).

    All users who access the app with this link have Consumer permissions. Note that you can revoke access to users accessing the link by clicking Generate new link (2). You will need to share the new link to provide those users with access again.

The App Usage tab displays the number of users who viewed the application over the specified time range, as well as user activity.

To select a different time range for the chart, open the Time range dropdown and select a new option. The chart automatically updates.

Updated November 15, 2022
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