Show AI Accelerator Predictions on Lightning Experience Record Pages
After your admin configures use cases on the AI Accelerator Setup page, show the predictions on a Lightning Experience page by adding the Einstein Predictions Using AI Accelerator Lightning App Builder component. Configure the scorecard component by selecting the use case, the prediction definition, the feature extractor, and other settings.
Required Editions
| Available in: Lightning Experience |
| User Permissions Needed | |
|---|---|
| To create and save pages in Lightning App Builder: | Customize Applicatiom |
Tip You can show only predictions on the AI Accelerator—Einstein Predictions
& Recommendations component scorecard, too. See Show AI Accelerator Predictions and NBA Recommendations on Lightning Experience Record
Pages.
Before you add the Einstein Predictions Using AI Accelerator Lightning App Builder component to a page, find the feature data type specified on the AI Accelerator Setup page.
- Open a record page of the primary response object selected in the AI Accelerator Setup page.
-
Click
, and
then select Edit Page.
- In Lightning App Builder, drag the Einstein Predictions Using AI Accelerator component onto your preferred location on the page.
-
In the component’s configuration panel, perform these steps:
- In the Use Case Definition field, select the use case whose predictions you want to embed in the page.
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In the Prediction field, select the model that you configured for your use case in
the AI Accelerator Setup page.
If you configured multiple models for your use case, select the model that best suits your requirements.
- For the model to use features available in the specified record ID, select Disable feature extraction.
-
If you want to use computed features, select the ID of a feature extractor.
To use the default feature extractor or the feature extractor in the use case configuration file, leave the Feature Extractor field blank.
- If the feature data type on the AI Accelerator Setup page is Real-Time Input or Batch Input, select Actual Feature Data as the feature data type.
-
If the feature data type on the AI Accelerator Setup page is Sample Input, select
Sample Feature Data as the feature data type.
Note If Disable feature extraction is selected, the feature data type isn’t considered. -
Configure these settings as necessary.
Property Description Show Prediction Label Shows the prediction label. Title A descriptive label for the prediction. Show title Shows the title of the prediction. Prediction score unit A unit of measure for the prediction. For example:
- Currency: For money-based predictions.
- Percentage: For probability-based predictions.
- Time interval: For time-based predictions, such as hours, days, and weeks.
Unit precedes score Shows units preceding the prediction, such as currency symbols. By default, units follow the prediction. Positive prediction label A label for the prediction when the prediction is higher than the threshold in a binary classification model. For example, Win, Retain, and Success. Negative prediction label A label to show when the prediction is lower than the threshold in a binary classification model. For example, Loss, Churn, and Fail. Show top predictors Shows the predictors with the highest impact on the prediction. Collapse details Shows top predictors but hides other details. Show ranked probabilities Shows ranked probabilities for outcome values. Applies only to predictions associated with multiclass classification models. Include link to model card Shows the Learn about this model link that users can click to see the model card associated with this prediction. For more information, see Configure the Model Card for a Prediction Definition. Show improvements Shows Einstein Discovery suggestions on how to improve the predicted outcome. Applies only to predictions associated with binary classification or numeric models. Number of improvements to show The maximum number of improvements returned on the prediction card. Applies only to predictions associated with binary classification or numeric models. Improvement threshold percentage A number to show only improvements that impact the predicted outcome by this percentage or higher. Applies only to predictions associated with binary classification or numeric models. Show values for predictors Shows the impact value next to predictors and improvements. Show prediction warnings Shows user warnings. User warnings include:
- Missing fields that are required for the model
- Field values that are outside the valid range that's used to build the predictive model
Calculate prediction as a date Shows time-based predictions as based on a relative start date and an offset value (the original prediction result). Start calculating date prediction from The date from when you want to start generating predictions. Time period The unit for the offset value—original prediction result—that's used to calculate the predicted date:
- Minutes
- Hours
- Days
- Weeks
- Months
Predicted date format The predicted date format:
- Time Remaining: Formats the prediction according to the selected period.
- Specific Date: Formats the prediction as a date according to the logged-in user’s locale settings.
Show prediction history starting from A reference point to show score history, such as:
- Last change
- Last week
Set Component Visibility Component visibility rules for a device, record field, or other field.
- Save your work, and then activate the page.
Users can view the predictions for the use case on the Lightning Experience record page in real time.
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