Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

Tabular monitoring objective.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective

Returns a new instance of GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective.



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34580

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#feature_attribution_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec

Feature attribution monitoring spec. Corresponds to the JSON property featureAttributionSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34560

def feature_attribution_spec
  @feature_attribution_spec
end

#feature_drift_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec

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. Corresponds to the JSON property featureDriftSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34569

def feature_drift_spec
  @feature_drift_spec
end

#prediction_output_drift_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec

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. Corresponds to the JSON property predictionOutputDriftSpec

Returns:



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34578

def prediction_output_drift_spec
  @prediction_output_drift_spec
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34585

def update!(**args)
  @feature_attribution_spec = args[:feature_attribution_spec] if args.key?(:feature_attribution_spec)
  @feature_drift_spec = args[:feature_drift_spec] if args.key?(:feature_drift_spec)
  @prediction_output_drift_spec = args[:prediction_output_drift_spec] if args.key?(:prediction_output_drift_spec)
end