Adding adaptive model predictors
Create predictors which are input fields for the adaptive models. When creating an adaptive model, select a wide range of fields that can potentially act as predictors.
The ADM service automatically determines which predictors are used by the models, based on the individual predictive performance and the correlation between predictors. For example, the predictors with a low predictive performance do not become active. When predictors are highly correlated, only the best-performing predictor is used.
The adaptive models accept two types of predictors: symbolic and numeric. The type of predictor is automatically populated when a property is included, but you can change the predictor type, if required. For example, if the contract duration, an integer value, has a value of either 12 or 24 months, you can change the predictor type from numeric, the default, to symbolic.
- Adding a predictor to an adaptive model
Select properties that you want to use as predictors in your adaptive model.
- Adding multiple predictors to an adaptive model
Use the batch option to add multiple predictors that you want to use in your adaptive model. You can define any number of properties as predictors.
- Adding 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.
- Enabling predefined Interaction History predictors for existing adaptive models
Apply historical interactions data to improve adaptive model predictions of future customer behavior, by enabling an additional set of potential predictors based on a predefined Interaction History summary.