After your exported model has been used for inference and it has saved model inputs and predictions to a supported data store, you can configure the model to monitor for data drift and model quality in Domino.
See Model Requirements and Set up Model Monitor.
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In the navigation pane, click Exports.
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Click the name of the Export for which you want to set up monitoring.
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Go to the Version History tab to confirm that the model is done exporting. If the model export is still in progress, wait until it is done before configuring monitoring.
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Click Monitoring.
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Click Configure Monitoring > Data.
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From the Configure Data window, select the Training Data and the Version for the Domino training set on which the model was trained. See Domino Training Sets.
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From Model type, select Classification or Regression depending on your model type. If your Training Set code includes prediction data defined in target_columns, select the model type that matches your Training Set:
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If target_columns is a categorical column, select Classification.
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If target_columns is a numerical column, select Regression.
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After the model is registered, the system shows options to add Prediction Data and Ground Truth Data.
NoteWhen the data is ingested, click the open this model link for the data to add.
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Click Save.
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See Test defaults to set the targets for your data drift and model quality metrics.
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Click Next.
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See Set Scheduled Checks to define the schedule for when monitoring results are calculated and updated.
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Click Next.
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To send email notifications if thresholds are breached based on the Scheduled checks, in Send alerts to these email addresses, type or paste a comma- or semicolon-separated list of email addresses.
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Click Save & Test.