Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

Extracting historical responses from adaptive models

Updated on July 5, 2022

Extract historical customer responses from adaptive models in your application for offline analysis. You can also build a model in a machine learning service of your choice, based on the historical responses that you extract.

When you enable the recording of historical data for a selected adaptive model, Pega Platform extracts historical customer responses from the model, and then stores the responses as a JSON file in a repository of your choice for 30 days. You can store the JSON file for a longer or shorter period of time by configuring the corresponding dynamic system setting.

By default, Pega Platform extracts historical responses only from adaptive models in production environments. You can enable the extraction of historical responses in non-production environments, for example, to test your workflow.

Before you begin:
  1. Determine where you want to save the historical data JSON files by specifying a repository for adaptive models data.

    For more information, see Specifying a repository for Prediction Studio models.

  2. If you want to extract historical data in non-production level environments too, change the value of the decision/adm/archiving/captureProductionLevel dynamic system setting to All.

    You can also extract historical data only in a selected production level environment by setting the decision/adm/archiving/captureProductionLevel dynamic system setting to a corresponding level number, for example, 5 for development environments. For a list of production level numbers, see Specifying the production level.

Enable recording historical data for a selected adaptive model.
  1. In the navigation pane of Prediction Studio, click Models.
  2. In the Models workspace, open the adaptive model for which you want to record historical data.
  3. In the Settings tab, in the Recording historical data section, select the Record historical data check box.
  4. In the Sample percentage sections, specify what percentage of all positive and negative customer responses you want to sample for the historical data JSON file:
    1. In the Positive outcome field, enter a percentage for positive outcomes.
    2. In the Negative outcome field, enter a percentage for negative outcomes.
    Note: The higher the sample percentage, the more space you need for storing the data set.

    To sample all historical customer responses, enter 100.0 in both fields.

    For example: A web banner typically has a significantly lower number of positive responses (banner clicks), than negative responses (banner impressions). In such cases, you can specify the sample percentage as follows:
    • Positive outcome100.0 %
    • Negative outcome1.0 %
  5. Confirm your settings by clicking Save.
  6. To change how much time elapses between saving a historical data JSON file and deleting the file from your repository, change the value of the decision/adm/archiving/daysToKeepData dynamic system setting.
    Important: By default, Pega Platform deletes JSON files with a time stamp older than 30 days.
  7. Optional: To access a list of all adaptive models along with the path of the historical data repository, in the navigation pane of Prediction Studio, click DataHistorical data.
    On the Historical data screen, you can also access information about the percentage of positive and negative responses that Pega Platform includes for each adaptive model.
What to do next: Learn more about the structure of the JSON file in which Pega Platform saves the historical data. For more information, see JSON file structure for historical data.

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us