Adaptive model tab on the Adaptive Model form
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.
- Model context
The context for adaptive models is defined by selecting properties from the top level Strategy Results (SR) class of your application as model identifiers. The model identifiers are used to partition adaptive models. Each unique combination of model identifiers creates an instance of an adaptive model that is associated to this Adaptive Model rule. For example, each proposition typically has its own model.
- Adding adaptive model predictors
When creating an adaptive model, select a wide range of fields that can potentially act as predictors. In the course of the learning process, adaptive models automatically select the best-performing predictors, which become active. The remaining predictors become inactive. Predictors are input fields for adaptive models.
- Parameterized predictors
To use input fields that are not available on the primary page where the rule is defined, but which are on the Strategy Results page (SR), configure these input fields as parameterized predictors for an adaptive model. If you do not specify parameterized predictors, your adaptive model can learn only from properties that are defined within the primary page context.
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