Defining outcome values in an adaptive model
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 Interaction rule that runs the strategy with the adaptive models that are configured by the Adaptive Model rule.
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.
In the navigation pane of Prediction Studio, click Models.
Open an adaptive model that you want to edit and click the Outcomes tab.
In the Outcomes tab, select the values in the outcome dimensions:
For Positive outcome, enter Accept, True, or Good. For Negative outcome, enter Reject, False, or Bad.
In the Positive outcome section, click Add outcome, and enter a value, for example,
In the Negative outcome section, click Add outcome, and enter a value, for example, Reject, False, Bad.
Confirm the new outcome values by clicking Save.
- Adaptive analytics
Adaptive Decision Manager (ADM) uses self-learning models to predict customer behavior. Adaptive models are used in decision strategies to increase the relevance of decisions.