Vertex AI v1beta1 API - Class ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue (1.0.0-beta73) 

public sealed class ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue : IMessage<ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue>, IEquatable<ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue>, IDeepCloneable<ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue>, IBufferMessage, IMessage

Reference documentation and code samples for the Vertex AI v1beta1 API class ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue.

Summary statistics for a population of values.

Inheritance

object > ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue

Namespace

Google.Cloud.AIPlatform.V1Beta1

Assembly

Google.Cloud.AIPlatform.V1Beta1.dll

Constructors

DistributionDataValue()

public DistributionDataValue()

DistributionDataValue(DistributionDataValue)

public DistributionDataValue(ModelMonitoringStatsDataPoint.Types.TypedValue.Types.DistributionDataValue other)
Parameter
Name Description
other ModelMonitoringStatsDataPointTypesTypedValueTypesDistributionDataValue

Properties

Distribution

public Value Distribution { get; set; }

Predictive monitoring drift distribution in tensorflow.metadata.v0.DatasetFeatureStatistics format.

Property Value
Type Description
Value

DistributionDeviation

public double DistributionDeviation { get; set; }

Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics.

  • For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen–Shannon divergence.
  • For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
Property Value
Type Description
double