Class FeatureAttributionSpec (1.117.0)
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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.
|