Model DataApp
Last updated
Last updated
Use this procedure to create a model DataApp in a project. After you run the data pipeline for any of these four problem types such as binary classification, regression, multi-class classification, or binary experimental problems, the DataApp button gets enabled.
Hover over the menu icon and select Projects
Select the project for which you want to create DataApps and click the DataApps icon from the project level navigation.
If no DataApps are available, you will see a screen with options - Custom DataApps or Import DataApps.
Click the plus icon and select Custom DataApp. Alternatively, click Custom DataApp in the DataApp workspace.
Select Model DataApp from the inputs.
Specify this information:
DataApp Name: The name of the DataApp.
DataApp Description: The description of the DataApp.
Recipe Name: The recipe for which you want to create a DataApp.
Environment: By default, the environment selected during project creation is applied. However, you have the flexibility to choose a different environment for running your DataApps.
Choose Image: Click to upload an image to display on the DataApp card that you see on the DataApps page.
Enter Model controls in the text box to provide specific context to the AI guide. This helps in aligning the AI-generated responses more closely with the user’s particular use case.
Toggle ON the Show Model Response Code option to view the code generated by the model in response to the queries.
Enable Allow Column Hyperlinks to create hyperlinks between columns in related tables.
Click Create.
You can see the DataApp card created in this project.
Use this procedure to view the dataapps created on the UI or published by Notebook users from Notebook.
Hover over the menu icon and select DataApps. This displays the dataapps dashboard where you can see all the DataApps for different projects in this tenant.
Note: The DataApps will become inactive after a certain period set by the admin. If you want to use DataApps, you must relaunch.
Click Relaunch on the DataApp card that you want to launch again.
Click on the Dataapp. The screen displays the following tabs:
Feature importance - Assigning scores to input features based on how helpful they are in predicting a target variable. These scores are ranked to help users understand which features have a significant impact on model prediction.
Model performance - This evaluates the performance of the model.
What-If analysis - Help data scientists to get insights into what a model predicts for given input values. This allows them to experiment with various combinations of values for key features and observe the resulting predictions.
You can use the sliders to change the values or use drop-down to select values and click Predict What-If Outcome to review what the model predicts for the given input values.
Prediction - You can perform predictions on the uploaded dataset. For more information, see Performing predictions on the uploaded dataset.
Use this procedure to do the predictions on the new dataset and generate charts using Ask AI.
Click Browse to upload the dataset and obtain predictions generated by the model.
Click Upload File From Local. Once you upload the file, click Close to upload.
Click Generate Prediction. Once the prediction is done on the dataset, you can download the prediction results, using the Download option.
Note: You can use the Log option to view the detailed records of the execution activity and identify issues.
Click Ask AI button.
This takes you to the Ask AI tab where you can provide the query in the query box and click the Generate button. You can query the dataset to generate charts on the dataset generated after predictions.
Important: Apart from generating charts, you can also perform data transformation operations on the dataset by prompting for the Ask AI.
Here is the output chart generated for the given query.
Click +DataApp to add this chart to the dataapp. The Update Name box appears where you can provide the custom name for the chart and click Save.
Click the User Charts tab to view this chart.
Ask AI - You can use the Ask AI feature similar to what you see in AI-assisted recipe to provide text prompt in the chat window and generate the chart outputs on the dataset used for model building. This allows you to generate visualizations and carry out different data pre-processing operations on the selected dataset.
You can add as many chats as you want and switch between the chat windows from the Chat list on the left. The difference between the chat window used for prediction output dataset and dataset used for model building can be see in its chat name on the left.
Perform the following actions clicking the Actions drop-down:
Copy the dataapps URL to share with the other business users, using the Copy option.
Open the dataapps on a new tab, using the Open in New Tab option.
Configure the shutdown time of the DataApp, using the Config option.
View logs of DataApps to debug issues, using the Logs option.
Delete the DataApp that is no longer required, using the Delete option.
Customize the branding appearance of your DataApp, using the Branding option. This opens the Branding modal. Enter your desired title in the DataApp Title field, then use the Upload from Computer option to upload your logo. Once you have added the title and logo, click Save to apply the changes. The customized title and logo will now appear on the AskAI page and will also be visible when the DataApp is opened in a new tab.
