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Defining outcome values in an adaptive model

Updated on March 11, 2021

Define the possible outcome values in an adaptive model to associate them with positive or negative behavior. The values defined for positive and negative outcome should coincide with the outcome definition as configured in the data flow that runs the strategy with the adaptive models that are configured by the Adaptive Model rule.

Note: For more information, switch your workspace to Dev Studio and access the Dev Studio help system.

Adaptive model learning is based on the outcome dimension in the Interaction History. The behavior dimension could be defined by the behavior level (for example, Positive) or combination of behavior and response (for example, Positive-Accepted). Adaptive models upgraded to the Pega Platform preserve the value corresponding to the response level in the behavior dimension (for example, Accepted), but not the value corresponding to the behavior level.

  1. In the navigation pane of Prediction Studio, click Models.
  2. Open an adaptive model that you want to edit and click the Outcomes tab.
  3. In the Outcomes tab, select the values in the outcome dimensions:
    1. In the Positive outcome section, click Add outcome, and enter a value, for example,
    2. In the Negative outcome section, click Add outcome, and enter a value, for example, Reject, False, Bad.
    For example: For Positive outcome, enter Accept, True, or Good. For Negative outcome, enter Reject, False, or Bad.
  4. Confirm the new outcome values by clicking Save.
Result: The models in the Adaptive Decision Manager (ADM) server that are configured by this adaptive model learn from the settings defined in the Positive outcome and Negative outcome sections.

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