Customer AI displays errors when model training, scoring, and configuration fails. In the Service instances section, a column for LAST RUN STATUS displays one of the following messages: Success, Training issue, and Failed.
In the event that Failed or Training issue is displayed, you can select the run status to open a side panel. The side panel contains your Last run status and Last run details. Last run details contains information on why the run failed. In the event that Customer AI is not able to provide details on your error, contact support with the error code thats provided.
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If you receive the error “Model Quality is poor. We recommend creating a new app with the modified configuration”. Follow the recommended steps below to help troubleshoot.
“Model quality is poor” means that the model accuracy is not within an acceptable range. Customer AI was unable to build a reliable model and AUC (Area under the ROC curve) < 0.65 after training. To fix the error, it is recommended that you change one of the configuration parameters and rerun the training.
Start by checking the accuracy of your data. It is important that your data contains the necessary fields needed for your predictive outcome.
If your data does not seem to be the problem, try changing the eligibility population condition to restrict the model to certain profiles (for example,
_experience.analytics.customDimensions.eVars.eVar142 exists in last 56 Days). This restricts the population and size of the data used in the training window.
If restricting the eligibility population did not work or is not possible, change your prediction window.