Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies

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

Historical Stats (and Anomalies) for a specific Feature.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies

Returns a new instance of GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies.



16877
16878
16879
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16877

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

Instance Attribute Details

#feature_display_name ⇒ String

Display Name of the Feature. Corresponds to the JSON property featureDisplayName

Returns:

  • (String) 


16852
16853
16854
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16852

def feature_display_name
  @feature_display_name
end

#prediction_stats ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1FeatureStatsAnomaly>

A list of historical stats generated by different time window's Prediction Dataset. Corresponds to the JSON property predictionStats

Returns:



16858
16859
16860
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16858

def prediction_stats
  @prediction_stats
end

#threshold ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ThresholdConfig

The config for feature monitoring threshold. Corresponds to the JSON property threshold

Returns:



16863
16864
16865
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16863

def threshold
  @threshold
end

#training_stats ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1FeatureStatsAnomaly

Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display. Corresponds to the JSON property trainingStats

Returns:



16875
16876
16877
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16875

def training_stats
  @training_stats
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



16882
16883
16884
16885
16886
16887
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 16882

def update!(**args)
  @feature_display_name = args[:feature_display_name] if args.key?(:feature_display_name)
  @prediction_stats = args[:prediction_stats] if args.key?(:prediction_stats)
  @threshold = args[:threshold] if args.key?(:threshold)
  @training_stats = args[:training_stats] if args.key?(:training_stats)
end