Arize AI
Default Actuals
Default predictions with no corresponding actual label to your negative class actual label.

Default Actuals

For some use cases, it may be important to treat a prediction for which no corresponding actual label has been logged yet as having a default negative class actual label. For example, consider tracking advertisement conversion rates for an ad clickthrough rate model, where the positive class is click and the negative class is no_click. For ad conversion purposes, a prediction without a corresponding actual label for an ad placement is equivalent to logging an explicit no_click actual label for the prediction. In both cases, the result is the same: a user has not converted by clicking on the ad. For AUC-ROC, PR-AUC, and Log Loss performance metrics, Arize supports treating predictions without an explicit actual label as having the negative class actual label by default. In the above example, a click prediction without an actual would be treated as a false positive, because the missing actual for the prediction would by default be assigned to the no_click negative class.
This feature can be enabled for monitors and dashboards via the model performance config section of your model's config page.

Set up Default Actuals via Config

Navigate to the Config tab to turn on default actuals and indicate your positive class.
Questions? Email us at [email protected] or Slack us in the #arize-support channel