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.
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.
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