- 1.75.0 (latest)
- 1.74.0
- 1.73.0
- 1.72.0
- 1.71.1
- 1.70.0
- 1.69.0
- 1.68.0
- 1.67.1
- 1.66.0
- 1.65.0
- 1.63.0
- 1.62.0
- 1.60.0
- 1.59.0
- 1.58.0
- 1.57.0
- 1.56.0
- 1.55.0
- 1.54.1
- 1.53.0
- 1.52.0
- 1.51.0
- 1.50.0
- 1.49.0
- 1.48.0
- 1.47.0
- 1.46.0
- 1.45.0
- 1.44.0
- 1.43.0
- 1.39.0
- 1.38.1
- 1.37.0
- 1.36.4
- 1.35.0
- 1.34.0
- 1.33.1
- 1.32.0
- 1.31.1
- 1.30.1
- 1.29.0
- 1.28.1
- 1.27.1
- 1.26.1
- 1.25.0
- 1.24.1
- 1.23.0
- 1.22.1
- 1.21.0
- 1.20.0
- 1.19.1
- 1.18.3
- 1.17.1
- 1.16.1
- 1.15.1
- 1.14.0
- 1.13.1
- 1.12.1
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.1
- 1.7.1
- 1.6.2
- 1.5.0
- 1.4.3
- 1.3.0
- 1.2.0
- 1.1.1
- 1.0.1
- 0.9.0
- 0.8.0
- 0.7.1
- 0.6.0
- 0.5.1
- 0.4.0
- 0.3.1
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.
|