다음을 통해 공유

FeatureAttributionDriftMonitoringSignal Constructors

  • Reference

Definition

Namespace:
Azure.ResourceManager.MachineLearning.Models
Assembly:
Azure.ResourceManager.MachineLearning.dll
Package:
Azure.ResourceManager.MachineLearning v1.2.0-beta.3
Package:
Azure.ResourceManager.MachineLearning v1.2.1

Overloads

FeatureAttributionDriftMonitoringSignal(FeatureAttributionMetricThreshold, IEnumerable<MonitoringInputDataBase>, MonitoringInputDataBase)

Initializes a new instance of FeatureAttributionDriftMonitoringSignal.
FeatureAttributionDriftMonitoringSignal(FeatureAttributionMetricThreshold, FeatureImportanceSettings, IEnumerable<MonitoringInputDataBase>, MonitoringInputDataBase)

Initializes a new instance of FeatureAttributionDriftMonitoringSignal.

FeatureAttributionDriftMonitoringSignal(FeatureAttributionMetricThreshold, IEnumerable<MonitoringInputDataBase>, MonitoringInputDataBase)

Source:
FeatureAttributionDriftMonitoringSignal.cs

Initializes a new instance of FeatureAttributionDriftMonitoringSignal.

public FeatureAttributionDriftMonitoringSignal (Azure.ResourceManager.MachineLearning.Models.FeatureAttributionMetricThreshold metricThreshold, System.Collections.Generic.IEnumerable<Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase> productionData, Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase referenceData);
new Azure.ResourceManager.MachineLearning.Models.FeatureAttributionDriftMonitoringSignal : Azure.ResourceManager.MachineLearning.Models.FeatureAttributionMetricThreshold * seq<Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase> * Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase -> Azure.ResourceManager.MachineLearning.Models.FeatureAttributionDriftMonitoringSignal
Public Sub New (metricThreshold As FeatureAttributionMetricThreshold, productionData As IEnumerable(Of MonitoringInputDataBase), referenceData As MonitoringInputDataBase)

Parameters

metricThreshold
FeatureAttributionMetricThreshold

[Required] A list of metrics to calculate and their associated thresholds.

productionData
IEnumerable<MonitoringInputDataBase>

[Required] The data which drift will be calculated for. Please note MonitoringInputDataBase is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include FixedInputData, StaticInputData and TrailingInputData.

referenceData
MonitoringInputDataBase

[Required] The data to calculate drift against. Please note MonitoringInputDataBase is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include FixedInputData, StaticInputData and TrailingInputData.

Exceptions

ArgumentNullException

metricThreshold, productionData or referenceData is null.

Applies to

FeatureAttributionDriftMonitoringSignal(FeatureAttributionMetricThreshold, FeatureImportanceSettings, IEnumerable<MonitoringInputDataBase>, MonitoringInputDataBase)

Source:
FeatureAttributionDriftMonitoringSignal.cs

Initializes a new instance of FeatureAttributionDriftMonitoringSignal.

public FeatureAttributionDriftMonitoringSignal (Azure.ResourceManager.MachineLearning.Models.FeatureAttributionMetricThreshold metricThreshold, Azure.ResourceManager.MachineLearning.Models.FeatureImportanceSettings featureImportanceSettings, System.Collections.Generic.IEnumerable<Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase> productionData, Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase referenceData);
new Azure.ResourceManager.MachineLearning.Models.FeatureAttributionDriftMonitoringSignal : Azure.ResourceManager.MachineLearning.Models.FeatureAttributionMetricThreshold * Azure.ResourceManager.MachineLearning.Models.FeatureImportanceSettings * seq<Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase> * Azure.ResourceManager.MachineLearning.Models.MonitoringInputDataBase -> Azure.ResourceManager.MachineLearning.Models.FeatureAttributionDriftMonitoringSignal
Public Sub New (metricThreshold As FeatureAttributionMetricThreshold, featureImportanceSettings As FeatureImportanceSettings, productionData As IEnumerable(Of MonitoringInputDataBase), referenceData As MonitoringInputDataBase)

Parameters

metricThreshold
FeatureAttributionMetricThreshold

[Required] A list of metrics to calculate and their associated thresholds.

featureImportanceSettings
FeatureImportanceSettings

[Required] The settings for computing feature importance.

productionData
IEnumerable<MonitoringInputDataBase>

[Required] The data which drift will be calculated for. Please note MonitoringInputDataBase is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include FixedInputData, RollingInputData and StaticInputData.

referenceData
MonitoringInputDataBase

[Required] The data to calculate drift against. Please note MonitoringInputDataBase is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include FixedInputData, RollingInputData and StaticInputData.

Exceptions

ArgumentNullException

metricThreshold, featureImportanceSettings, productionData or referenceData is null.

Applies to