Class FeatureAttributionSpec (1.73.0)

FeatureAttributionSpec(
    features: typing.Optional[typing.List[str]] = None,
    default_alert_threshold: typing.Optional[float] = None,
    feature_alert_thresholds: typing.Optional[typing.Dict[str, float]] = None,
    batch_dedicated_resources: typing.Optional[
        google.cloud.aiplatform_v1beta1.types.machine_resources.BatchDedicatedResources
    ] = None,
)

Feature attribution spec.

.. rubric:: Example

feature_attribution_spec=FeatureAttributionSpec( features=["feature1"] default_alert_threshold=0.01, feature_alert_thresholds={"feature1":0.02, "feature2":0.01}, batch_dedicated_resources=BatchDedicatedResources( starting_replica_count=1, max_replica_count=2, machine_spec=my_machine_spec, ), )

Attributes
Name	Description
`features`	`List[str]` Optional. Input feature names interested in monitoring. These should be a subset of the input feature names specified in the monitoring schema. If not specified, all features outlied in the monitoring schema will be used.
`default_alert_threshold`	`float` Optional. Default alert threshold for all the features.
`feature_alert_thresholds`	`Dict[str, float]` Optional. Per feature alert threshold will override default alert threshold.
`batch_dedicated_resources`	`machine_resources.BatchDedicatedResources` Optional. 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.

Class FeatureAttributionSpec (1.73.0)

Attributes