TabularObjective Stay organized with collections Save and categorize content based on your preferences.
Tabular monitoring objective.
featureDriftSpecobject (DataDriftSpec)Input feature distribution drift monitoring spec.
predictionOutputDriftSpecobject (DataDriftSpec)Prediction output distribution drift monitoring spec.
featureAttributionSpecobject (FeatureAttributionSpec)feature attribution monitoring spec.
| JSON representation |
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{"featureDriftSpec":{object ( |
DataDriftSpec
data drift monitoring spec. data drift measures the distribution distance between the current dataset and a baseline dataset. A typical use case is to detect data drift between the recent production serving dataset and the training dataset, or to compare the recent production dataset with a dataset from a previous period.
features[]stringfeature names / Prediction output names interested in monitoring. These should be a subset of the input feature names or prediction output names specified in the monitoring schema. If the field is not specified all features / prediction outputs outlied in the monitoring schema will be used.
categoricalMetricTypestringSupported metrics type: * l_infinity * jensen_shannon_divergence
numericMetricTypestringSupported metrics type: * jensen_shannon_divergence
defaultCategoricalAlertConditionobject (ModelMonitoringAlertCondition)Default alert condition for all the categorical features.
defaultNumericAlertConditionobject (ModelMonitoringAlertCondition)Default alert condition for all the numeric features.
featureAlertConditionsmap (key: string, value: object (ModelMonitoringAlertCondition))Per feature alert condition will override default alert condition.
| JSON representation |
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{"features":[string],"categoricalMetricType":string,"numericMetricType":string,"defaultCategoricalAlertCondition":{object ( |
ModelMonitoringAlertCondition
Monitoring alert triggered condition.
conditionUnion typecondition can be only one of the following:thresholdnumberA condition that compares a stats value against a threshold. Alert will be triggered if value above the threshold.
| JSON representation |
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{// condition"threshold":number// Union type} |
FeatureAttributionSpec
feature attribution monitoring spec.
features[]stringfeature names interested in monitoring. These should be a subset of the input feature names specified in the monitoring schema. If the field is not specified all features outlied in the monitoring schema will be used.
defaultAlertConditionobject (ModelMonitoringAlertCondition)Default alert condition for all the features.
featureAlertConditionsmap (key: string, value: object (ModelMonitoringAlertCondition))Per feature alert condition will override default alert condition.
batchExplanationDedicatedResourcesobject (BatchDedicatedResources)The config of resources used by the Model Monitoring during the batch explanation for non-AutoML models. If not set,n1-standard-2 machine type will be used by default.
| JSON representation |
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{"features":[string],"defaultAlertCondition":{object ( |
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Last updated 2025-06-27 UTC.