public sealed class FeaturestoreMonitoringConfig.Types.ThresholdConfig : IMessage<FeaturestoreMonitoringConfig.Types.ThresholdConfig>, IEquatable<FeaturestoreMonitoringConfig.Types.ThresholdConfig>, IDeepCloneable<FeaturestoreMonitoringConfig.Types.ThresholdConfig>, IBufferMessage, IMessageReference documentation and code samples for the Vertex AI v1 API class FeaturestoreMonitoringConfig.Types.ThresholdConfig.
The config for Featurestore Monitoring threshold.
Implements
IMessageFeaturestoreMonitoringConfigTypesThresholdConfig, IEquatableFeaturestoreMonitoringConfigTypesThresholdConfig, IDeepCloneableFeaturestoreMonitoringConfigTypesThresholdConfig, IBufferMessage, IMessageNamespace
Google.Cloud.AIPlatform.V1Assembly
Google.Cloud.AIPlatform.V1.dll
Constructors
ThresholdConfig()
public ThresholdConfig()ThresholdConfig(ThresholdConfig)
public ThresholdConfig(FeaturestoreMonitoringConfig.Types.ThresholdConfig other)| Parameter | |
|---|---|
| Name | Description |
other |
FeaturestoreMonitoringConfigTypesThresholdConfig |
Properties
HasValue
public bool HasValue { get; }Gets whether the "value" field is set
| Property Value | |
|---|---|
| Type | Description |
bool |
|
ThresholdCase
public FeaturestoreMonitoringConfig.Types.ThresholdConfig.ThresholdOneofCase ThresholdCase { get; }| Property Value | |
|---|---|
| Type | Description |
FeaturestoreMonitoringConfigTypesThresholdConfigThresholdOneofCase |
|
Value
public double Value { get; set; }Specify a threshold value that can trigger the alert.
- For categorical feature, the distribution distance is calculated by L-inifinity norm.
- For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
| Property Value | |
|---|---|
| Type | Description |
double |
|