Class: Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig
- Includes:
- Core::Hashable, Core::JsonObjectSupport
- Defined in:
- lib/google/apis/aiplatform_v1/classes.rb,
lib/google/apis/aiplatform_v1/representations.rb,
lib/google/apis/aiplatform_v1/representations.rb
Overview
The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.
Instance Attribute Summary collapse
-
#explanation_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig
The config for integrating with Vertex Explainable AI.
-
#prediction_drift_detection_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig
The config for Prediction data drift detection.
-
#training_dataset ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset
Training Dataset information.
-
#training_prediction_skew_detection_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig
The config for Training & Prediction data skew detection.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig
constructor
A new instance of GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig
Returns a new instance of GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig.
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16026 def initialize(**args) update!(**args) end |
Instance Attribute Details
#explanation_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig
The config for integrating with Vertex Explainable AI. Only applicable if the
Model has explanation_spec populated.
Corresponds to the JSON property explanationConfig
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16008 def explanation_config @explanation_config end |
#prediction_drift_detection_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig
The config for Prediction data drift detection.
Corresponds to the JSON property predictionDriftDetectionConfig
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16013 def prediction_drift_detection_config @prediction_drift_detection_config end |
#training_dataset ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset
Training Dataset information.
Corresponds to the JSON property trainingDataset
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16018 def training_dataset @training_dataset end |
#training_prediction_skew_detection_config ⇒ Google::Apis::AiplatformV1::GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig
The config for Training & Prediction data skew detection. It specifies the
training dataset sources and the skew detection parameters.
Corresponds to the JSON property trainingPredictionSkewDetectionConfig
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16024 def training_prediction_skew_detection_config @training_prediction_skew_detection_config end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/aiplatform_v1/classes.rb', line 16031 def update!(**args) @explanation_config = args[:explanation_config] if args.key?(:explanation_config) @prediction_drift_detection_config = args[:prediction_drift_detection_config] if args.key?(:prediction_drift_detection_config) @training_dataset = args[:training_dataset] if args.key?(:training_dataset) @training_prediction_skew_detection_config = args[:training_prediction_skew_detection_config] if args.key?(:training_prediction_skew_detection_config) end |