Obtaining predictor information
Use the Call instruction with the DSMPublicAPI-ADM.pxLoadPredictorInfo activity to obtain the predictor information of an adaptive model. Predictors contain information about the cases whose values might potentially show some association with the behavior that you are trying to predict.
Examples of predictor information include:
- Demographic - Age, gender, and marital status.
- Financial - Income and expenditure.
- Activity or transaction information - The amount of a loan or the price of the product.
Create an instance of the Activity rule by clicking.
In the activity steps, enter the Call DSMPublicAPI-ADM.pxLoadPredictorInfo method.
Click the arrow to the left of the Method field to expand the method and specify the option to include active, or active and inactive predictors by performing one of the following actions:
- Set it to true to retrieve only active predictors.
- Set it to false to retrieve active and inactive predictors.
Specify the Result page to store predictor information.
Specify the Adaptive model key page.This page must be on the Embed-Decision-AdaptiveModel-Key class to uniquely identify an adaptive model. The properties of data type text in this class provide the action dimension ( pyIssue, pyGroup, and pyName ), channel dimension ( pyDirection, and pyChannel ), the applies to class of the adaptive model ( pyConfigurationAppliesTo ), and the name of the adaptive model ( pyConfigurationName ).
- Calling another activity
A keystore is a file that contains keys and certificates that you use for encryption, authentication, and serving content over HTTPS. In Pega Platform, you create a keystore data instance that points to a keystore file.
- 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.
- Decision Management methods