Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ThresholdConfig.
The config for Featurestore Monitoring threshold.
Generated from protobuf message google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ThresholdConfig
Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ value |
float
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. 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. |
getValue
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.
Generated from protobuf field double value = 1;
| Returns | |
|---|---|
| Type | Description |
float | |
hasValue
setValue
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.
Generated from protobuf field double value = 1;
| Parameter | |
|---|---|
| Name | Description |
var |
float
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getThreshold
| Returns | |
|---|---|
| Type | Description |
string | |