Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ThresholdConfig.
The config for feature monitoring threshold.
Generated from protobuf message google.cloud.aiplatform.v1.ThresholdConfig
Methods
__construct
Constructor.
Parameters | |
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Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ value |
float
Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 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.
If this threshold config is for feature distribution distance:
- 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.
Returns | |
---|---|
Type | Description |
float |
hasValue
setValue
Specify a threshold value that can trigger the alert.
If this threshold config is for feature distribution distance:
- 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.
Parameter | |
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Name | Description |
var |
float
|
Returns | |
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Type | Description |
$this |
getThreshold
Returns | |
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Type | Description |
string |