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.



13697
13698
13699
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13697

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) 


13672
13673
13674
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13672

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:



13678
13679
13680
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13678

def prediction_stats
  @prediction_stats
end

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

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

Returns:



13683
13684
13685
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13683

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:



13695
13696
13697
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13695

def training_stats
  @training_stats
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



13702
13703
13704
13705
13706
13707
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 13702

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