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Troubleshooting an adaptive model with no active predictors

Beginning with Pega Platform 8.4, Prediction Studio sends a notification when an adaptive model instance does not have any active predictors. An adaptive model without active predictors does not have predictive power, and so does not provide predictive results. Improve model performance by identifying and addressing the root cause of the issue. The possible root causes include a lack of defined predictors, the model continuing to collect a sufficient number of responses, or the low predictive performance of the model predictors.

Notification text

Adaptive Model modelName Model has no active predictors.

Recommended next steps

Identify and address the root cause of the issue by performing the following procedures:

Ensure that you define predictors for the adaptive model

  1. In Prediction Studio, open the adaptive model by clicking the corresponding notification.
  2. On the Predictors tab, verify the number of predictors:
    • If there are no defined predictors, add predictors to the adaptive model by clicking Add field, and then specifying the predictor properties.
    • If there is at least one defined predictor, see Verify the number of registered responses.

Verify the number of registered responses

  1. In Prediction Studio, open the adaptive model by clicking the corresponding notification.
  2. On the Monitor tab, for the affected model instance, click Model report.
  3. Expand the Model details section, and then, in the Number of responses section, verify the number of responses that the model instance registered for each response type:
    • If each response type has less than 100 responses, wait until the model receives more responses.
    • If each response type has more than 100 responses, go to step 4 in Verify predictor performance.

Verify predictor performance

  1. In Prediction Studio, open the adaptive model by clicking the corresponding notification.
  2. On the Monitor tab, for the affected model instance, click Model report.
  3. On the Predictors tab, if all or most predictors have a predictive performance score below 52 Area Under the Curve (AUC), add predictors that potentially have a higher correlation with the outcome.

    For more information, see Adding a predictor to an adaptive model.

 

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