On the Adaptive Model tab, you can define the basic settings of an Adaptive Model rule instance by performing the tasks, such as defining the model context and potential predictors. You can also view the parameterized predictors.
- Define model context
- An adaptive model rule is a configuration that controls multiple ADM models. The model context consists of one or more model identifiers, for example, issue, group, and proposition name. This configuration generates models for each unique set of model identifiers. If separate models are needed in different channels, then that channel can be added to the model context.
- Define potential predictors
- Predictors are fields from within the primary page context that act as input for adaptive learning. For each model, the ADM service selects active predictors from the list of potential predictors, based on the performance of the predictors and their correlations. For more information, see predictors.
- View the parameterized predictors
- Parameterized predictors are parameters from outside of the primary page context that you can configure as additional input in the adaptive learning process. These parameters can be proposition attributes from the Strategy Results (SR) class. For more information, see Parameterized predictors.